Documentation ¶
Index ¶
- Variables
- func RegisterModelServiceServer(s *grpc.Server, srv ModelServiceServer)
- type DeleteModelRequest
- func (*DeleteModelRequest) Descriptor() ([]byte, []int)deprecated
- func (x *DeleteModelRequest) GetDatasetId() string
- func (x *DeleteModelRequest) GetModelId() string
- func (x *DeleteModelRequest) GetProjectId() string
- func (*DeleteModelRequest) ProtoMessage()
- func (x *DeleteModelRequest) ProtoReflect() protoreflect.Message
- func (x *DeleteModelRequest) Reset()
- func (x *DeleteModelRequest) String() string
- type EncryptionConfiguration
- func (*EncryptionConfiguration) Descriptor() ([]byte, []int)deprecated
- func (x *EncryptionConfiguration) GetKmsKeyName() *wrapperspb.StringValue
- func (*EncryptionConfiguration) ProtoMessage()
- func (x *EncryptionConfiguration) ProtoReflect() protoreflect.Message
- func (x *EncryptionConfiguration) Reset()
- func (x *EncryptionConfiguration) String() string
- type GetModelRequest
- func (*GetModelRequest) Descriptor() ([]byte, []int)deprecated
- func (x *GetModelRequest) GetDatasetId() string
- func (x *GetModelRequest) GetModelId() string
- func (x *GetModelRequest) GetProjectId() string
- func (*GetModelRequest) ProtoMessage()
- func (x *GetModelRequest) ProtoReflect() protoreflect.Message
- func (x *GetModelRequest) Reset()
- func (x *GetModelRequest) String() string
- type ListModelsRequest
- func (*ListModelsRequest) Descriptor() ([]byte, []int)deprecated
- func (x *ListModelsRequest) GetDatasetId() string
- func (x *ListModelsRequest) GetMaxResults() *wrapperspb.UInt32Value
- func (x *ListModelsRequest) GetPageToken() string
- func (x *ListModelsRequest) GetProjectId() string
- func (*ListModelsRequest) ProtoMessage()
- func (x *ListModelsRequest) ProtoReflect() protoreflect.Message
- func (x *ListModelsRequest) Reset()
- func (x *ListModelsRequest) String() string
- type ListModelsResponse
- func (*ListModelsResponse) Descriptor() ([]byte, []int)deprecated
- func (x *ListModelsResponse) GetModels() []*Model
- func (x *ListModelsResponse) GetNextPageToken() string
- func (*ListModelsResponse) ProtoMessage()
- func (x *ListModelsResponse) ProtoReflect() protoreflect.Message
- func (x *ListModelsResponse) Reset()
- func (x *ListModelsResponse) String() string
- type Model
- func (*Model) Descriptor() ([]byte, []int)deprecated
- func (x *Model) GetCreationTime() int64
- func (x *Model) GetDescription() string
- func (x *Model) GetEncryptionConfiguration() *EncryptionConfiguration
- func (x *Model) GetEtag() string
- func (x *Model) GetExpirationTime() int64
- func (x *Model) GetFeatureColumns() []*StandardSqlField
- func (x *Model) GetFriendlyName() string
- func (x *Model) GetLabelColumns() []*StandardSqlField
- func (x *Model) GetLabels() map[string]string
- func (x *Model) GetLastModifiedTime() int64
- func (x *Model) GetLocation() string
- func (x *Model) GetModelReference() *ModelReference
- func (x *Model) GetModelType() Model_ModelType
- func (x *Model) GetTrainingRuns() []*Model_TrainingRun
- func (*Model) ProtoMessage()
- func (x *Model) ProtoReflect() protoreflect.Message
- func (x *Model) Reset()
- func (x *Model) String() string
- type ModelReference
- func (*ModelReference) Descriptor() ([]byte, []int)deprecated
- func (x *ModelReference) GetDatasetId() string
- func (x *ModelReference) GetModelId() string
- func (x *ModelReference) GetProjectId() string
- func (*ModelReference) ProtoMessage()
- func (x *ModelReference) ProtoReflect() protoreflect.Message
- func (x *ModelReference) Reset()
- func (x *ModelReference) String() string
- type ModelServiceClient
- type ModelServiceServer
- type Model_AggregateClassificationMetrics
- func (*Model_AggregateClassificationMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_AggregateClassificationMetrics) GetAccuracy() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetF1Score() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetLogLoss() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetPrecision() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetRecall() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetRocAuc() *wrapperspb.DoubleValue
- func (x *Model_AggregateClassificationMetrics) GetThreshold() *wrapperspb.DoubleValue
- func (*Model_AggregateClassificationMetrics) ProtoMessage()
- func (x *Model_AggregateClassificationMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_AggregateClassificationMetrics) Reset()
- func (x *Model_AggregateClassificationMetrics) String() string
- type Model_ArimaFittingMetrics
- func (*Model_ArimaFittingMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ArimaFittingMetrics) GetAic() float64
- func (x *Model_ArimaFittingMetrics) GetLogLikelihood() float64
- func (x *Model_ArimaFittingMetrics) GetVariance() float64
- func (*Model_ArimaFittingMetrics) ProtoMessage()
- func (x *Model_ArimaFittingMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_ArimaFittingMetrics) Reset()
- func (x *Model_ArimaFittingMetrics) String() string
- type Model_ArimaForecastingMetrics
- func (*Model_ArimaForecastingMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ArimaForecastingMetrics) GetArimaFittingMetrics() []*Model_ArimaFittingMetrics
- func (x *Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics() []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics
- func (x *Model_ArimaForecastingMetrics) GetHasDrift() []bool
- func (x *Model_ArimaForecastingMetrics) GetNonSeasonalOrder() []*Model_ArimaOrder
- func (x *Model_ArimaForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
- func (x *Model_ArimaForecastingMetrics) GetTimeSeriesId() []string
- func (*Model_ArimaForecastingMetrics) ProtoMessage()
- func (x *Model_ArimaForecastingMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_ArimaForecastingMetrics) Reset()
- func (x *Model_ArimaForecastingMetrics) String() string
- type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics
- func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics() *Model_ArimaFittingMetrics
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift() bool
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder() *Model_ArimaOrder
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId() string
- func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage()
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset()
- func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String() string
- type Model_ArimaOrder
- func (*Model_ArimaOrder) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ArimaOrder) GetD() int64
- func (x *Model_ArimaOrder) GetP() int64
- func (x *Model_ArimaOrder) GetQ() int64
- func (*Model_ArimaOrder) ProtoMessage()
- func (x *Model_ArimaOrder) ProtoReflect() protoreflect.Message
- func (x *Model_ArimaOrder) Reset()
- func (x *Model_ArimaOrder) String() string
- type Model_BinaryClassificationMetrics
- func (*Model_BinaryClassificationMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics
- func (x *Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList() []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix
- func (x *Model_BinaryClassificationMetrics) GetNegativeLabel() string
- func (x *Model_BinaryClassificationMetrics) GetPositiveLabel() string
- func (*Model_BinaryClassificationMetrics) ProtoMessage()
- func (x *Model_BinaryClassificationMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_BinaryClassificationMetrics) Reset()
- func (x *Model_BinaryClassificationMetrics) String() string
- type Model_BinaryClassificationMetrics_BinaryConfusionMatrix
- func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor() ([]byte, []int)deprecated
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy() *wrapperspb.DoubleValue
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score() *wrapperspb.DoubleValue
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives() *wrapperspb.Int64Value
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives() *wrapperspb.Int64Value
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold() *wrapperspb.DoubleValue
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision() *wrapperspb.DoubleValue
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall() *wrapperspb.DoubleValue
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives() *wrapperspb.Int64Value
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives() *wrapperspb.Int64Value
- func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage()
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect() protoreflect.Message
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset()
- func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String() string
- type Model_ClusteringMetrics
- func (*Model_ClusteringMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ClusteringMetrics) GetClusters() []*Model_ClusteringMetrics_Cluster
- func (x *Model_ClusteringMetrics) GetDaviesBouldinIndex() *wrapperspb.DoubleValue
- func (x *Model_ClusteringMetrics) GetMeanSquaredDistance() *wrapperspb.DoubleValue
- func (*Model_ClusteringMetrics) ProtoMessage()
- func (x *Model_ClusteringMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_ClusteringMetrics) Reset()
- func (x *Model_ClusteringMetrics) String() string
- type Model_ClusteringMetrics_Cluster
- func (*Model_ClusteringMetrics_Cluster) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ClusteringMetrics_Cluster) GetCentroidId() int64
- func (x *Model_ClusteringMetrics_Cluster) GetCount() *wrapperspb.Int64Value
- func (x *Model_ClusteringMetrics_Cluster) GetFeatureValues() []*Model_ClusteringMetrics_Cluster_FeatureValue
- func (*Model_ClusteringMetrics_Cluster) ProtoMessage()
- func (x *Model_ClusteringMetrics_Cluster) ProtoReflect() protoreflect.Message
- func (x *Model_ClusteringMetrics_Cluster) Reset()
- func (x *Model_ClusteringMetrics_Cluster) String() string
- type Model_ClusteringMetrics_Cluster_FeatureValue
- func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue() *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn() string
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue() *wrapperspb.DoubleValue
- func (m *Model_ClusteringMetrics_Cluster_FeatureValue) GetValue() isModel_ClusteringMetrics_Cluster_FeatureValue_Value
- func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect() protoreflect.Message
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) Reset()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue) String() string
- type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue
- func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts() []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount
- func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect() protoreflect.Message
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String() string
- type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_
- type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount
- func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor() ([]byte, []int)deprecated
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory() string
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount() *wrapperspb.Int64Value
- func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect() protoreflect.Message
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Reset()
- func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) String() string
- type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue
- type Model_DataFrequency
- func (Model_DataFrequency) Descriptor() protoreflect.EnumDescriptor
- func (x Model_DataFrequency) Enum() *Model_DataFrequency
- func (Model_DataFrequency) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_DataFrequency) Number() protoreflect.EnumNumber
- func (x Model_DataFrequency) String() string
- func (Model_DataFrequency) Type() protoreflect.EnumType
- type Model_DataSplitMethod
- func (Model_DataSplitMethod) Descriptor() protoreflect.EnumDescriptor
- func (x Model_DataSplitMethod) Enum() *Model_DataSplitMethod
- func (Model_DataSplitMethod) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_DataSplitMethod) Number() protoreflect.EnumNumber
- func (x Model_DataSplitMethod) String() string
- func (Model_DataSplitMethod) Type() protoreflect.EnumType
- type Model_DataSplitResult
- func (*Model_DataSplitResult) Descriptor() ([]byte, []int)deprecated
- func (x *Model_DataSplitResult) GetEvaluationTable() *TableReference
- func (x *Model_DataSplitResult) GetTrainingTable() *TableReference
- func (*Model_DataSplitResult) ProtoMessage()
- func (x *Model_DataSplitResult) ProtoReflect() protoreflect.Message
- func (x *Model_DataSplitResult) Reset()
- func (x *Model_DataSplitResult) String() string
- type Model_DistanceType
- func (Model_DistanceType) Descriptor() protoreflect.EnumDescriptor
- func (x Model_DistanceType) Enum() *Model_DistanceType
- func (Model_DistanceType) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_DistanceType) Number() protoreflect.EnumNumber
- func (x Model_DistanceType) String() string
- func (Model_DistanceType) Type() protoreflect.EnumType
- type Model_EvaluationMetrics
- func (*Model_EvaluationMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_EvaluationMetrics) GetArimaForecastingMetrics() *Model_ArimaForecastingMetrics
- func (x *Model_EvaluationMetrics) GetBinaryClassificationMetrics() *Model_BinaryClassificationMetrics
- func (x *Model_EvaluationMetrics) GetClusteringMetrics() *Model_ClusteringMetrics
- func (m *Model_EvaluationMetrics) GetMetrics() isModel_EvaluationMetrics_Metrics
- func (x *Model_EvaluationMetrics) GetMultiClassClassificationMetrics() *Model_MultiClassClassificationMetrics
- func (x *Model_EvaluationMetrics) GetRankingMetrics() *Model_RankingMetrics
- func (x *Model_EvaluationMetrics) GetRegressionMetrics() *Model_RegressionMetrics
- func (*Model_EvaluationMetrics) ProtoMessage()
- func (x *Model_EvaluationMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_EvaluationMetrics) Reset()
- func (x *Model_EvaluationMetrics) String() string
- type Model_EvaluationMetrics_ArimaForecastingMetrics
- type Model_EvaluationMetrics_BinaryClassificationMetrics
- type Model_EvaluationMetrics_ClusteringMetrics
- type Model_EvaluationMetrics_MultiClassClassificationMetrics
- type Model_EvaluationMetrics_RankingMetrics
- type Model_EvaluationMetrics_RegressionMetrics
- type Model_FeedbackType
- func (Model_FeedbackType) Descriptor() protoreflect.EnumDescriptor
- func (x Model_FeedbackType) Enum() *Model_FeedbackType
- func (Model_FeedbackType) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_FeedbackType) Number() protoreflect.EnumNumber
- func (x Model_FeedbackType) String() string
- func (Model_FeedbackType) Type() protoreflect.EnumType
- type Model_GlobalExplanation
- func (*Model_GlobalExplanation) Descriptor() ([]byte, []int)deprecated
- func (x *Model_GlobalExplanation) GetClassLabel() string
- func (x *Model_GlobalExplanation) GetExplanations() []*Model_GlobalExplanation_Explanation
- func (*Model_GlobalExplanation) ProtoMessage()
- func (x *Model_GlobalExplanation) ProtoReflect() protoreflect.Message
- func (x *Model_GlobalExplanation) Reset()
- func (x *Model_GlobalExplanation) String() string
- type Model_GlobalExplanation_Explanation
- func (*Model_GlobalExplanation_Explanation) Descriptor() ([]byte, []int)deprecated
- func (x *Model_GlobalExplanation_Explanation) GetAttribution() *wrapperspb.DoubleValue
- func (x *Model_GlobalExplanation_Explanation) GetFeatureName() string
- func (*Model_GlobalExplanation_Explanation) ProtoMessage()
- func (x *Model_GlobalExplanation_Explanation) ProtoReflect() protoreflect.Message
- func (x *Model_GlobalExplanation_Explanation) Reset()
- func (x *Model_GlobalExplanation_Explanation) String() string
- type Model_HolidayRegion
- func (Model_HolidayRegion) Descriptor() protoreflect.EnumDescriptor
- func (x Model_HolidayRegion) Enum() *Model_HolidayRegion
- func (Model_HolidayRegion) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_HolidayRegion) Number() protoreflect.EnumNumber
- func (x Model_HolidayRegion) String() string
- func (Model_HolidayRegion) Type() protoreflect.EnumType
- type Model_KmeansEnums
- type Model_KmeansEnums_KmeansInitializationMethod
- func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor() protoreflect.EnumDescriptor
- func (x Model_KmeansEnums_KmeansInitializationMethod) Enum() *Model_KmeansEnums_KmeansInitializationMethod
- func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_KmeansEnums_KmeansInitializationMethod) Number() protoreflect.EnumNumber
- func (x Model_KmeansEnums_KmeansInitializationMethod) String() string
- func (Model_KmeansEnums_KmeansInitializationMethod) Type() protoreflect.EnumType
- type Model_LearnRateStrategy
- func (Model_LearnRateStrategy) Descriptor() protoreflect.EnumDescriptor
- func (x Model_LearnRateStrategy) Enum() *Model_LearnRateStrategy
- func (Model_LearnRateStrategy) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_LearnRateStrategy) Number() protoreflect.EnumNumber
- func (x Model_LearnRateStrategy) String() string
- func (Model_LearnRateStrategy) Type() protoreflect.EnumType
- type Model_LossType
- func (Model_LossType) Descriptor() protoreflect.EnumDescriptor
- func (x Model_LossType) Enum() *Model_LossType
- func (Model_LossType) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_LossType) Number() protoreflect.EnumNumber
- func (x Model_LossType) String() string
- func (Model_LossType) Type() protoreflect.EnumType
- type Model_ModelType
- func (Model_ModelType) Descriptor() protoreflect.EnumDescriptor
- func (x Model_ModelType) Enum() *Model_ModelType
- func (Model_ModelType) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_ModelType) Number() protoreflect.EnumNumber
- func (x Model_ModelType) String() string
- func (Model_ModelType) Type() protoreflect.EnumType
- type Model_MultiClassClassificationMetrics
- func (*Model_MultiClassClassificationMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics
- func (x *Model_MultiClassClassificationMetrics) GetConfusionMatrixList() []*Model_MultiClassClassificationMetrics_ConfusionMatrix
- func (*Model_MultiClassClassificationMetrics) ProtoMessage()
- func (x *Model_MultiClassClassificationMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_MultiClassClassificationMetrics) Reset()
- func (x *Model_MultiClassClassificationMetrics) String() string
- type Model_MultiClassClassificationMetrics_ConfusionMatrix
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor() ([]byte, []int)deprecated
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold() *wrapperspb.DoubleValue
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetRows() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect() protoreflect.Message
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) String() string
- type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor() ([]byte, []int)deprecated
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount() *wrapperspb.Int64Value
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel() string
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect() protoreflect.Message
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String() string
- type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor() ([]byte, []int)deprecated
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel() string
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetEntries() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry
- func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect() protoreflect.Message
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset()
- func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String() string
- type Model_OptimizationStrategy
- func (Model_OptimizationStrategy) Descriptor() protoreflect.EnumDescriptor
- func (x Model_OptimizationStrategy) Enum() *Model_OptimizationStrategy
- func (Model_OptimizationStrategy) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_OptimizationStrategy) Number() protoreflect.EnumNumber
- func (x Model_OptimizationStrategy) String() string
- func (Model_OptimizationStrategy) Type() protoreflect.EnumType
- type Model_RankingMetrics
- func (*Model_RankingMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_RankingMetrics) GetAverageRank() *wrapperspb.DoubleValue
- func (x *Model_RankingMetrics) GetMeanAveragePrecision() *wrapperspb.DoubleValue
- func (x *Model_RankingMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue
- func (x *Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain() *wrapperspb.DoubleValue
- func (*Model_RankingMetrics) ProtoMessage()
- func (x *Model_RankingMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_RankingMetrics) Reset()
- func (x *Model_RankingMetrics) String() string
- type Model_RegressionMetrics
- func (*Model_RegressionMetrics) Descriptor() ([]byte, []int)deprecated
- func (x *Model_RegressionMetrics) GetMeanAbsoluteError() *wrapperspb.DoubleValue
- func (x *Model_RegressionMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue
- func (x *Model_RegressionMetrics) GetMeanSquaredLogError() *wrapperspb.DoubleValue
- func (x *Model_RegressionMetrics) GetMedianAbsoluteError() *wrapperspb.DoubleValue
- func (x *Model_RegressionMetrics) GetRSquared() *wrapperspb.DoubleValue
- func (*Model_RegressionMetrics) ProtoMessage()
- func (x *Model_RegressionMetrics) ProtoReflect() protoreflect.Message
- func (x *Model_RegressionMetrics) Reset()
- func (x *Model_RegressionMetrics) String() string
- type Model_SeasonalPeriod
- type Model_SeasonalPeriod_SeasonalPeriodType
- func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor() protoreflect.EnumDescriptor
- func (x Model_SeasonalPeriod_SeasonalPeriodType) Enum() *Model_SeasonalPeriod_SeasonalPeriodType
- func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor() ([]byte, []int)deprecated
- func (x Model_SeasonalPeriod_SeasonalPeriodType) Number() protoreflect.EnumNumber
- func (x Model_SeasonalPeriod_SeasonalPeriodType) String() string
- func (Model_SeasonalPeriod_SeasonalPeriodType) Type() protoreflect.EnumType
- type Model_TrainingRun
- func (*Model_TrainingRun) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun) GetDataSplitResult() *Model_DataSplitResult
- func (x *Model_TrainingRun) GetEvaluationMetrics() *Model_EvaluationMetrics
- func (x *Model_TrainingRun) GetGlobalExplanations() []*Model_GlobalExplanation
- func (x *Model_TrainingRun) GetResults() []*Model_TrainingRun_IterationResult
- func (x *Model_TrainingRun) GetStartTime() *timestamppb.Timestamp
- func (x *Model_TrainingRun) GetTrainingOptions() *Model_TrainingRun_TrainingOptions
- func (*Model_TrainingRun) ProtoMessage()
- func (x *Model_TrainingRun) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun) Reset()
- func (x *Model_TrainingRun) String() string
- type Model_TrainingRun_IterationResult
- func (*Model_TrainingRun_IterationResult) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_IterationResult) GetArimaResult() *Model_TrainingRun_IterationResult_ArimaResult
- func (x *Model_TrainingRun_IterationResult) GetClusterInfos() []*Model_TrainingRun_IterationResult_ClusterInfo
- func (x *Model_TrainingRun_IterationResult) GetDurationMs() *wrapperspb.Int64Value
- func (x *Model_TrainingRun_IterationResult) GetEvalLoss() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_IterationResult) GetIndex() *wrapperspb.Int32Value
- func (x *Model_TrainingRun_IterationResult) GetLearnRate() float64
- func (x *Model_TrainingRun_IterationResult) GetTrainingLoss() *wrapperspb.DoubleValue
- func (*Model_TrainingRun_IterationResult) ProtoMessage()
- func (x *Model_TrainingRun_IterationResult) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_IterationResult) Reset()
- func (x *Model_TrainingRun_IterationResult) String() string
- type Model_TrainingRun_IterationResult_ArimaResult
- func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo() []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo
- func (x *Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
- func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage()
- func (x *Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_IterationResult_ArimaResult) Reset()
- func (x *Model_TrainingRun_IterationResult_ArimaResult) String() string
- type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients
- func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients() []float64
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient() float64
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients() []float64
- func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage()
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset()
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String() string
- type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo
- func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients() *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics() *Model_ArimaFittingMetrics
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift() bool
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder() *Model_ArimaOrder
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId() string
- func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage()
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset()
- func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String() string
- type Model_TrainingRun_IterationResult_ClusterInfo
- func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId() int64
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize() *wrapperspb.Int64Value
- func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage()
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) Reset()
- func (x *Model_TrainingRun_IterationResult_ClusterInfo) String() string
- type Model_TrainingRun_TrainingOptions
- func (*Model_TrainingRun_TrainingOptions) Descriptor() ([]byte, []int)deprecated
- func (x *Model_TrainingRun_TrainingOptions) GetAutoArima() bool
- func (x *Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder() int64
- func (x *Model_TrainingRun_TrainingOptions) GetBatchSize() int64
- func (x *Model_TrainingRun_TrainingOptions) GetDataFrequency() Model_DataFrequency
- func (x *Model_TrainingRun_TrainingOptions) GetDataSplitColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction() float64
- func (x *Model_TrainingRun_TrainingOptions) GetDataSplitMethod() Model_DataSplitMethod
- func (x *Model_TrainingRun_TrainingOptions) GetDistanceType() Model_DistanceType
- func (x *Model_TrainingRun_TrainingOptions) GetDropout() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetEarlyStop() *wrapperspb.BoolValue
- func (x *Model_TrainingRun_TrainingOptions) GetFeedbackType() Model_FeedbackType
- func (x *Model_TrainingRun_TrainingOptions) GetHiddenUnits() []int64
- func (x *Model_TrainingRun_TrainingOptions) GetHolidayRegion() Model_HolidayRegion
- func (x *Model_TrainingRun_TrainingOptions) GetHorizon() int64
- func (x *Model_TrainingRun_TrainingOptions) GetIncludeDrift() bool
- func (x *Model_TrainingRun_TrainingOptions) GetInitialLearnRate() float64
- func (x *Model_TrainingRun_TrainingOptions) GetInputLabelColumns() []string
- func (x *Model_TrainingRun_TrainingOptions) GetItemColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod() Model_KmeansEnums_KmeansInitializationMethod
- func (x *Model_TrainingRun_TrainingOptions) GetL1Regularization() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetL2Regularization() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetLabelClassWeights() map[string]float64
- func (x *Model_TrainingRun_TrainingOptions) GetLearnRate() float64
- func (x *Model_TrainingRun_TrainingOptions) GetLearnRateStrategy() Model_LearnRateStrategy
- func (x *Model_TrainingRun_TrainingOptions) GetLossType() Model_LossType
- func (x *Model_TrainingRun_TrainingOptions) GetMaxIterations() int64
- func (x *Model_TrainingRun_TrainingOptions) GetMaxTreeDepth() int64
- func (x *Model_TrainingRun_TrainingOptions) GetMinRelativeProgress() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetMinSplitLoss() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetModelUri() string
- func (x *Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder() *Model_ArimaOrder
- func (x *Model_TrainingRun_TrainingOptions) GetNumClusters() int64
- func (x *Model_TrainingRun_TrainingOptions) GetNumFactors() int64
- func (x *Model_TrainingRun_TrainingOptions) GetOptimizationStrategy() Model_OptimizationStrategy
- func (x *Model_TrainingRun_TrainingOptions) GetPreserveInputStructs() bool
- func (x *Model_TrainingRun_TrainingOptions) GetSubsample() float64
- func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetUserColumn() string
- func (x *Model_TrainingRun_TrainingOptions) GetWalsAlpha() *wrapperspb.DoubleValue
- func (x *Model_TrainingRun_TrainingOptions) GetWarmStart() *wrapperspb.BoolValue
- func (*Model_TrainingRun_TrainingOptions) ProtoMessage()
- func (x *Model_TrainingRun_TrainingOptions) ProtoReflect() protoreflect.Message
- func (x *Model_TrainingRun_TrainingOptions) Reset()
- func (x *Model_TrainingRun_TrainingOptions) String() string
- type PatchModelRequest
- func (*PatchModelRequest) Descriptor() ([]byte, []int)deprecated
- func (x *PatchModelRequest) GetDatasetId() string
- func (x *PatchModelRequest) GetModel() *Model
- func (x *PatchModelRequest) GetModelId() string
- func (x *PatchModelRequest) GetProjectId() string
- func (*PatchModelRequest) ProtoMessage()
- func (x *PatchModelRequest) ProtoReflect() protoreflect.Message
- func (x *PatchModelRequest) Reset()
- func (x *PatchModelRequest) String() string
- type StandardSqlDataType
- func (*StandardSqlDataType) Descriptor() ([]byte, []int)deprecated
- func (x *StandardSqlDataType) GetArrayElementType() *StandardSqlDataType
- func (x *StandardSqlDataType) GetStructType() *StandardSqlStructType
- func (m *StandardSqlDataType) GetSubType() isStandardSqlDataType_SubType
- func (x *StandardSqlDataType) GetTypeKind() StandardSqlDataType_TypeKind
- func (*StandardSqlDataType) ProtoMessage()
- func (x *StandardSqlDataType) ProtoReflect() protoreflect.Message
- func (x *StandardSqlDataType) Reset()
- func (x *StandardSqlDataType) String() string
- type StandardSqlDataType_ArrayElementType
- type StandardSqlDataType_StructType
- type StandardSqlDataType_TypeKind
- func (StandardSqlDataType_TypeKind) Descriptor() protoreflect.EnumDescriptor
- func (x StandardSqlDataType_TypeKind) Enum() *StandardSqlDataType_TypeKind
- func (StandardSqlDataType_TypeKind) EnumDescriptor() ([]byte, []int)deprecated
- func (x StandardSqlDataType_TypeKind) Number() protoreflect.EnumNumber
- func (x StandardSqlDataType_TypeKind) String() string
- func (StandardSqlDataType_TypeKind) Type() protoreflect.EnumType
- type StandardSqlField
- func (*StandardSqlField) Descriptor() ([]byte, []int)deprecated
- func (x *StandardSqlField) GetName() string
- func (x *StandardSqlField) GetType() *StandardSqlDataType
- func (*StandardSqlField) ProtoMessage()
- func (x *StandardSqlField) ProtoReflect() protoreflect.Message
- func (x *StandardSqlField) Reset()
- func (x *StandardSqlField) String() string
- type StandardSqlStructType
- func (*StandardSqlStructType) Descriptor() ([]byte, []int)deprecated
- func (x *StandardSqlStructType) GetFields() []*StandardSqlField
- func (*StandardSqlStructType) ProtoMessage()
- func (x *StandardSqlStructType) ProtoReflect() protoreflect.Message
- func (x *StandardSqlStructType) Reset()
- func (x *StandardSqlStructType) String() string
- type TableReference
- func (*TableReference) Descriptor() ([]byte, []int)deprecated
- func (x *TableReference) GetDatasetId() string
- func (x *TableReference) GetProjectId() string
- func (x *TableReference) GetTableId() string
- func (*TableReference) ProtoMessage()
- func (x *TableReference) ProtoReflect() protoreflect.Message
- func (x *TableReference) Reset()
- func (x *TableReference) String() string
- type UnimplementedModelServiceServer
- func (*UnimplementedModelServiceServer) DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error)
- func (*UnimplementedModelServiceServer) GetModel(context.Context, *GetModelRequest) (*Model, error)
- func (*UnimplementedModelServiceServer) ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
- func (*UnimplementedModelServiceServer) PatchModel(context.Context, *PatchModelRequest) (*Model, error)
Constants ¶
This section is empty.
Variables ¶
var ( Model_ModelType_name = map[int32]string{ 0: "MODEL_TYPE_UNSPECIFIED", 1: "LINEAR_REGRESSION", 2: "LOGISTIC_REGRESSION", 3: "KMEANS", 4: "MATRIX_FACTORIZATION", 5: "DNN_CLASSIFIER", 6: "TENSORFLOW", 7: "DNN_REGRESSOR", 9: "BOOSTED_TREE_REGRESSOR", 10: "BOOSTED_TREE_CLASSIFIER", 11: "ARIMA", 12: "AUTOML_REGRESSOR", 13: "AUTOML_CLASSIFIER", } Model_ModelType_value = map[string]int32{ "MODEL_TYPE_UNSPECIFIED": 0, "LINEAR_REGRESSION": 1, "LOGISTIC_REGRESSION": 2, "KMEANS": 3, "MATRIX_FACTORIZATION": 4, "DNN_CLASSIFIER": 5, "TENSORFLOW": 6, "DNN_REGRESSOR": 7, "BOOSTED_TREE_REGRESSOR": 9, "BOOSTED_TREE_CLASSIFIER": 10, "ARIMA": 11, "AUTOML_REGRESSOR": 12, "AUTOML_CLASSIFIER": 13, } )
Enum value maps for Model_ModelType.
var ( Model_LossType_name = map[int32]string{ 0: "LOSS_TYPE_UNSPECIFIED", 1: "MEAN_SQUARED_LOSS", 2: "MEAN_LOG_LOSS", } Model_LossType_value = map[string]int32{ "LOSS_TYPE_UNSPECIFIED": 0, "MEAN_SQUARED_LOSS": 1, "MEAN_LOG_LOSS": 2, } )
Enum value maps for Model_LossType.
var ( Model_DistanceType_name = map[int32]string{ 0: "DISTANCE_TYPE_UNSPECIFIED", 1: "EUCLIDEAN", 2: "COSINE", } Model_DistanceType_value = map[string]int32{ "DISTANCE_TYPE_UNSPECIFIED": 0, "EUCLIDEAN": 1, "COSINE": 2, } )
Enum value maps for Model_DistanceType.
var ( Model_DataSplitMethod_name = map[int32]string{ 0: "DATA_SPLIT_METHOD_UNSPECIFIED", 1: "RANDOM", 2: "CUSTOM", 3: "SEQUENTIAL", 4: "NO_SPLIT", 5: "AUTO_SPLIT", } Model_DataSplitMethod_value = map[string]int32{ "DATA_SPLIT_METHOD_UNSPECIFIED": 0, "RANDOM": 1, "CUSTOM": 2, "SEQUENTIAL": 3, "NO_SPLIT": 4, "AUTO_SPLIT": 5, } )
Enum value maps for Model_DataSplitMethod.
var ( Model_DataFrequency_name = map[int32]string{ 0: "DATA_FREQUENCY_UNSPECIFIED", 1: "AUTO_FREQUENCY", 2: "YEARLY", 3: "QUARTERLY", 4: "MONTHLY", 5: "WEEKLY", 6: "DAILY", 7: "HOURLY", } Model_DataFrequency_value = map[string]int32{ "DATA_FREQUENCY_UNSPECIFIED": 0, "AUTO_FREQUENCY": 1, "YEARLY": 2, "QUARTERLY": 3, "MONTHLY": 4, "WEEKLY": 5, "DAILY": 6, "HOURLY": 7, } )
Enum value maps for Model_DataFrequency.
var ( Model_HolidayRegion_name = map[int32]string{ 0: "HOLIDAY_REGION_UNSPECIFIED", 1: "GLOBAL", 2: "NA", 3: "JAPAC", 4: "EMEA", 5: "LAC", 6: "AE", 7: "AR", 8: "AT", 9: "AU", 10: "BE", 11: "BR", 12: "CA", 13: "CH", 14: "CL", 15: "CN", 16: "CO", 17: "CS", 18: "CZ", 19: "DE", 20: "DK", 21: "DZ", 22: "EC", 23: "EE", 24: "EG", 25: "ES", 26: "FI", 27: "FR", 28: "GB", 29: "GR", 30: "HK", 31: "HU", 32: "ID", 33: "IE", 34: "IL", 35: "IN", 36: "IR", 37: "IT", 38: "JP", 39: "KR", 40: "LV", 41: "MA", 42: "MX", 43: "MY", 44: "NG", 45: "NL", 46: "NO", 47: "NZ", 48: "PE", 49: "PH", 50: "PK", 51: "PL", 52: "PT", 53: "RO", 54: "RS", 55: "RU", 56: "SA", 57: "SE", 58: "SG", 59: "SI", 60: "SK", 61: "TH", 62: "TR", 63: "TW", 64: "UA", 65: "US", 66: "VE", 67: "VN", 68: "ZA", } Model_HolidayRegion_value = map[string]int32{ "HOLIDAY_REGION_UNSPECIFIED": 0, "GLOBAL": 1, "NA": 2, "JAPAC": 3, "EMEA": 4, "LAC": 5, "AE": 6, "AR": 7, "AT": 8, "AU": 9, "BE": 10, "BR": 11, "CA": 12, "CH": 13, "CL": 14, "CN": 15, "CO": 16, "CS": 17, "CZ": 18, "DE": 19, "DK": 20, "DZ": 21, "EC": 22, "EE": 23, "EG": 24, "ES": 25, "FI": 26, "FR": 27, "GB": 28, "GR": 29, "HK": 30, "HU": 31, "ID": 32, "IE": 33, "IL": 34, "IN": 35, "IR": 36, "IT": 37, "JP": 38, "KR": 39, "LV": 40, "MA": 41, "MX": 42, "MY": 43, "NG": 44, "NL": 45, "NO": 46, "NZ": 47, "PE": 48, "PH": 49, "PK": 50, "PL": 51, "PT": 52, "RO": 53, "RS": 54, "RU": 55, "SA": 56, "SE": 57, "SG": 58, "SI": 59, "SK": 60, "TH": 61, "TR": 62, "TW": 63, "UA": 64, "US": 65, "VE": 66, "VN": 67, "ZA": 68, } )
Enum value maps for Model_HolidayRegion.
var ( Model_LearnRateStrategy_name = map[int32]string{ 0: "LEARN_RATE_STRATEGY_UNSPECIFIED", 1: "LINE_SEARCH", 2: "CONSTANT", } Model_LearnRateStrategy_value = map[string]int32{ "LEARN_RATE_STRATEGY_UNSPECIFIED": 0, "LINE_SEARCH": 1, "CONSTANT": 2, } )
Enum value maps for Model_LearnRateStrategy.
var ( Model_OptimizationStrategy_name = map[int32]string{ 0: "OPTIMIZATION_STRATEGY_UNSPECIFIED", 1: "BATCH_GRADIENT_DESCENT", 2: "NORMAL_EQUATION", } Model_OptimizationStrategy_value = map[string]int32{ "OPTIMIZATION_STRATEGY_UNSPECIFIED": 0, "BATCH_GRADIENT_DESCENT": 1, "NORMAL_EQUATION": 2, } )
Enum value maps for Model_OptimizationStrategy.
var ( Model_FeedbackType_name = map[int32]string{ 0: "FEEDBACK_TYPE_UNSPECIFIED", 1: "IMPLICIT", 2: "EXPLICIT", } Model_FeedbackType_value = map[string]int32{ "FEEDBACK_TYPE_UNSPECIFIED": 0, "IMPLICIT": 1, "EXPLICIT": 2, } )
Enum value maps for Model_FeedbackType.
var ( Model_SeasonalPeriod_SeasonalPeriodType_name = map[int32]string{ 0: "SEASONAL_PERIOD_TYPE_UNSPECIFIED", 1: "NO_SEASONALITY", 2: "DAILY", 3: "WEEKLY", 4: "MONTHLY", 5: "QUARTERLY", 6: "YEARLY", } Model_SeasonalPeriod_SeasonalPeriodType_value = map[string]int32{ "SEASONAL_PERIOD_TYPE_UNSPECIFIED": 0, "NO_SEASONALITY": 1, "DAILY": 2, "WEEKLY": 3, "MONTHLY": 4, "QUARTERLY": 5, "YEARLY": 6, } )
Enum value maps for Model_SeasonalPeriod_SeasonalPeriodType.
var ( Model_KmeansEnums_KmeansInitializationMethod_name = map[int32]string{ 0: "KMEANS_INITIALIZATION_METHOD_UNSPECIFIED", 1: "RANDOM", 2: "CUSTOM", 3: "KMEANS_PLUS_PLUS", } Model_KmeansEnums_KmeansInitializationMethod_value = map[string]int32{ "KMEANS_INITIALIZATION_METHOD_UNSPECIFIED": 0, "RANDOM": 1, "CUSTOM": 2, "KMEANS_PLUS_PLUS": 3, } )
Enum value maps for Model_KmeansEnums_KmeansInitializationMethod.
var ( StandardSqlDataType_TypeKind_name = map[int32]string{ 0: "TYPE_KIND_UNSPECIFIED", 2: "INT64", 5: "BOOL", 7: "FLOAT64", 8: "STRING", 9: "BYTES", 19: "TIMESTAMP", 10: "DATE", 20: "TIME", 21: "DATETIME", 22: "GEOGRAPHY", 23: "NUMERIC", 24: "BIGNUMERIC", 16: "ARRAY", 17: "STRUCT", } StandardSqlDataType_TypeKind_value = map[string]int32{ "TYPE_KIND_UNSPECIFIED": 0, "INT64": 2, "BOOL": 5, "FLOAT64": 7, "STRING": 8, "BYTES": 9, "TIMESTAMP": 19, "DATE": 10, "TIME": 20, "DATETIME": 21, "GEOGRAPHY": 22, "NUMERIC": 23, "BIGNUMERIC": 24, "ARRAY": 16, "STRUCT": 17, } )
Enum value maps for StandardSqlDataType_TypeKind.
var File_google_cloud_bigquery_v2_encryption_config_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_model_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_model_reference_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_standard_sql_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_table_reference_proto protoreflect.FileDescriptor
Functions ¶
func RegisterModelServiceServer ¶
func RegisterModelServiceServer(s *grpc.Server, srv ModelServiceServer)
Types ¶
type DeleteModelRequest ¶
type DeleteModelRequest struct { // Required. Project ID of the model to delete. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. Dataset ID of the model to delete. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // Required. Model ID of the model to delete. ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"` // contains filtered or unexported fields }
func (*DeleteModelRequest) Descriptor
deprecated
func (*DeleteModelRequest) Descriptor() ([]byte, []int)
Deprecated: Use DeleteModelRequest.ProtoReflect.Descriptor instead.
func (*DeleteModelRequest) GetDatasetId ¶
func (x *DeleteModelRequest) GetDatasetId() string
func (*DeleteModelRequest) GetModelId ¶
func (x *DeleteModelRequest) GetModelId() string
func (*DeleteModelRequest) GetProjectId ¶
func (x *DeleteModelRequest) GetProjectId() string
func (*DeleteModelRequest) ProtoMessage ¶
func (*DeleteModelRequest) ProtoMessage()
func (*DeleteModelRequest) ProtoReflect ¶
func (x *DeleteModelRequest) ProtoReflect() protoreflect.Message
func (*DeleteModelRequest) Reset ¶
func (x *DeleteModelRequest) Reset()
func (*DeleteModelRequest) String ¶
func (x *DeleteModelRequest) String() string
type EncryptionConfiguration ¶
type EncryptionConfiguration struct { // Optional. Describes the Cloud KMS encryption key that will be used to // protect destination BigQuery table. The BigQuery Service Account associated // with your project requires access to this encryption key. KmsKeyName *wrapperspb.StringValue `protobuf:"bytes,1,opt,name=kms_key_name,json=kmsKeyName,proto3" json:"kms_key_name,omitempty"` // contains filtered or unexported fields }
func (*EncryptionConfiguration) Descriptor
deprecated
func (*EncryptionConfiguration) Descriptor() ([]byte, []int)
Deprecated: Use EncryptionConfiguration.ProtoReflect.Descriptor instead.
func (*EncryptionConfiguration) GetKmsKeyName ¶
func (x *EncryptionConfiguration) GetKmsKeyName() *wrapperspb.StringValue
func (*EncryptionConfiguration) ProtoMessage ¶
func (*EncryptionConfiguration) ProtoMessage()
func (*EncryptionConfiguration) ProtoReflect ¶
func (x *EncryptionConfiguration) ProtoReflect() protoreflect.Message
func (*EncryptionConfiguration) Reset ¶
func (x *EncryptionConfiguration) Reset()
func (*EncryptionConfiguration) String ¶
func (x *EncryptionConfiguration) String() string
type GetModelRequest ¶
type GetModelRequest struct { // Required. Project ID of the requested model. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. Dataset ID of the requested model. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // Required. Model ID of the requested model. ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"` // contains filtered or unexported fields }
func (*GetModelRequest) Descriptor
deprecated
func (*GetModelRequest) Descriptor() ([]byte, []int)
Deprecated: Use GetModelRequest.ProtoReflect.Descriptor instead.
func (*GetModelRequest) GetDatasetId ¶
func (x *GetModelRequest) GetDatasetId() string
func (*GetModelRequest) GetModelId ¶
func (x *GetModelRequest) GetModelId() string
func (*GetModelRequest) GetProjectId ¶
func (x *GetModelRequest) GetProjectId() string
func (*GetModelRequest) ProtoMessage ¶
func (*GetModelRequest) ProtoMessage()
func (*GetModelRequest) ProtoReflect ¶
func (x *GetModelRequest) ProtoReflect() protoreflect.Message
func (*GetModelRequest) Reset ¶
func (x *GetModelRequest) Reset()
func (*GetModelRequest) String ¶
func (x *GetModelRequest) String() string
type ListModelsRequest ¶
type ListModelsRequest struct { // Required. Project ID of the models to list. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. Dataset ID of the models to list. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // The maximum number of results to return in a single response page. // Leverage the page tokens to iterate through the entire collection. MaxResults *wrapperspb.UInt32Value `protobuf:"bytes,3,opt,name=max_results,json=maxResults,proto3" json:"max_results,omitempty"` // Page token, returned by a previous call to request the next page of // results PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"` // contains filtered or unexported fields }
func (*ListModelsRequest) Descriptor
deprecated
func (*ListModelsRequest) Descriptor() ([]byte, []int)
Deprecated: Use ListModelsRequest.ProtoReflect.Descriptor instead.
func (*ListModelsRequest) GetDatasetId ¶
func (x *ListModelsRequest) GetDatasetId() string
func (*ListModelsRequest) GetMaxResults ¶
func (x *ListModelsRequest) GetMaxResults() *wrapperspb.UInt32Value
func (*ListModelsRequest) GetPageToken ¶
func (x *ListModelsRequest) GetPageToken() string
func (*ListModelsRequest) GetProjectId ¶
func (x *ListModelsRequest) GetProjectId() string
func (*ListModelsRequest) ProtoMessage ¶
func (*ListModelsRequest) ProtoMessage()
func (*ListModelsRequest) ProtoReflect ¶
func (x *ListModelsRequest) ProtoReflect() protoreflect.Message
func (*ListModelsRequest) Reset ¶
func (x *ListModelsRequest) Reset()
func (*ListModelsRequest) String ¶
func (x *ListModelsRequest) String() string
type ListModelsResponse ¶
type ListModelsResponse struct { // Models in the requested dataset. Only the following fields are populated: // model_reference, model_type, creation_time, last_modified_time and // labels. Models []*Model `protobuf:"bytes,1,rep,name=models,proto3" json:"models,omitempty"` // A token to request the next page of results. NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"` // contains filtered or unexported fields }
func (*ListModelsResponse) Descriptor
deprecated
func (*ListModelsResponse) Descriptor() ([]byte, []int)
Deprecated: Use ListModelsResponse.ProtoReflect.Descriptor instead.
func (*ListModelsResponse) GetModels ¶
func (x *ListModelsResponse) GetModels() []*Model
func (*ListModelsResponse) GetNextPageToken ¶
func (x *ListModelsResponse) GetNextPageToken() string
func (*ListModelsResponse) ProtoMessage ¶
func (*ListModelsResponse) ProtoMessage()
func (*ListModelsResponse) ProtoReflect ¶
func (x *ListModelsResponse) ProtoReflect() protoreflect.Message
func (*ListModelsResponse) Reset ¶
func (x *ListModelsResponse) Reset()
func (*ListModelsResponse) String ¶
func (x *ListModelsResponse) String() string
type Model ¶
type Model struct { // Output only. A hash of this resource. Etag string `protobuf:"bytes,1,opt,name=etag,proto3" json:"etag,omitempty"` // Required. Unique identifier for this model. ModelReference *ModelReference `protobuf:"bytes,2,opt,name=model_reference,json=modelReference,proto3" json:"model_reference,omitempty"` // Output only. The time when this model was created, in millisecs since the epoch. CreationTime int64 `protobuf:"varint,5,opt,name=creation_time,json=creationTime,proto3" json:"creation_time,omitempty"` // Output only. The time when this model was last modified, in millisecs since the epoch. LastModifiedTime int64 `protobuf:"varint,6,opt,name=last_modified_time,json=lastModifiedTime,proto3" json:"last_modified_time,omitempty"` // Optional. A user-friendly description of this model. Description string `protobuf:"bytes,12,opt,name=description,proto3" json:"description,omitempty"` // Optional. A descriptive name for this model. FriendlyName string `protobuf:"bytes,14,opt,name=friendly_name,json=friendlyName,proto3" json:"friendly_name,omitempty"` // The labels associated with this model. You can use these to organize // and group your models. Label keys and values can be no longer // than 63 characters, can only contain lowercase letters, numeric // characters, underscores and dashes. International characters are allowed. // Label values are optional. Label keys must start with a letter and each // label in the list must have a different key. Labels map[string]string `` /* 154-byte string literal not displayed */ // Optional. The time when this model expires, in milliseconds since the epoch. // If not present, the model will persist indefinitely. Expired models // will be deleted and their storage reclaimed. The defaultTableExpirationMs // property of the encapsulating dataset can be used to set a default // expirationTime on newly created models. ExpirationTime int64 `protobuf:"varint,16,opt,name=expiration_time,json=expirationTime,proto3" json:"expiration_time,omitempty"` // Output only. The geographic location where the model resides. This value // is inherited from the dataset. Location string `protobuf:"bytes,13,opt,name=location,proto3" json:"location,omitempty"` // Custom encryption configuration (e.g., Cloud KMS keys). This shows the // encryption configuration of the model data while stored in BigQuery // storage. This field can be used with PatchModel to update encryption key // for an already encrypted model. EncryptionConfiguration *EncryptionConfiguration `` /* 131-byte string literal not displayed */ // Output only. Type of the model resource. ModelType Model_ModelType `` /* 135-byte string literal not displayed */ // Output only. Information for all training runs in increasing order of start_time. TrainingRuns []*Model_TrainingRun `protobuf:"bytes,9,rep,name=training_runs,json=trainingRuns,proto3" json:"training_runs,omitempty"` // Output only. Input feature columns that were used to train this model. FeatureColumns []*StandardSqlField `protobuf:"bytes,10,rep,name=feature_columns,json=featureColumns,proto3" json:"feature_columns,omitempty"` // Output only. Label columns that were used to train this model. // The output of the model will have a "predicted_" prefix to these columns. LabelColumns []*StandardSqlField `protobuf:"bytes,11,rep,name=label_columns,json=labelColumns,proto3" json:"label_columns,omitempty"` // contains filtered or unexported fields }
func (*Model) Descriptor
deprecated
func (*Model) GetCreationTime ¶
func (*Model) GetDescription ¶
func (*Model) GetEncryptionConfiguration ¶
func (x *Model) GetEncryptionConfiguration() *EncryptionConfiguration
func (*Model) GetExpirationTime ¶
func (*Model) GetFeatureColumns ¶
func (x *Model) GetFeatureColumns() []*StandardSqlField
func (*Model) GetFriendlyName ¶
func (*Model) GetLabelColumns ¶
func (x *Model) GetLabelColumns() []*StandardSqlField
func (*Model) GetLastModifiedTime ¶
func (*Model) GetLocation ¶
func (*Model) GetModelReference ¶
func (x *Model) GetModelReference() *ModelReference
func (*Model) GetModelType ¶
func (x *Model) GetModelType() Model_ModelType
func (*Model) GetTrainingRuns ¶
func (x *Model) GetTrainingRuns() []*Model_TrainingRun
func (*Model) ProtoMessage ¶
func (*Model) ProtoMessage()
func (*Model) ProtoReflect ¶
func (x *Model) ProtoReflect() protoreflect.Message
type ModelReference ¶
type ModelReference struct { // Required. The ID of the project containing this model. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. The ID of the dataset containing this model. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // Required. The ID of the model. The ID must contain only // letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum // length is 1,024 characters. ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"` // contains filtered or unexported fields }
Id path of a model.
func (*ModelReference) Descriptor
deprecated
func (*ModelReference) Descriptor() ([]byte, []int)
Deprecated: Use ModelReference.ProtoReflect.Descriptor instead.
func (*ModelReference) GetDatasetId ¶
func (x *ModelReference) GetDatasetId() string
func (*ModelReference) GetModelId ¶
func (x *ModelReference) GetModelId() string
func (*ModelReference) GetProjectId ¶
func (x *ModelReference) GetProjectId() string
func (*ModelReference) ProtoMessage ¶
func (*ModelReference) ProtoMessage()
func (*ModelReference) ProtoReflect ¶
func (x *ModelReference) ProtoReflect() protoreflect.Message
func (*ModelReference) Reset ¶
func (x *ModelReference) Reset()
func (*ModelReference) String ¶
func (x *ModelReference) String() string
type ModelServiceClient ¶
type ModelServiceClient interface { // Gets the specified model resource by model ID. GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error) // Lists all models in the specified dataset. Requires the READER dataset // role. ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error) // Patch specific fields in the specified model. PatchModel(ctx context.Context, in *PatchModelRequest, opts ...grpc.CallOption) (*Model, error) // Deletes the model specified by modelId from the dataset. DeleteModel(ctx context.Context, in *DeleteModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error) }
ModelServiceClient is the client API for ModelService service.
For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
func NewModelServiceClient ¶
func NewModelServiceClient(cc grpc.ClientConnInterface) ModelServiceClient
type ModelServiceServer ¶
type ModelServiceServer interface { // Gets the specified model resource by model ID. GetModel(context.Context, *GetModelRequest) (*Model, error) // Lists all models in the specified dataset. Requires the READER dataset // role. ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error) // Patch specific fields in the specified model. PatchModel(context.Context, *PatchModelRequest) (*Model, error) // Deletes the model specified by modelId from the dataset. DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error) }
ModelServiceServer is the server API for ModelService service.
type Model_AggregateClassificationMetrics ¶
type Model_AggregateClassificationMetrics struct { // Precision is the fraction of actual positive predictions that had // positive actual labels. For multiclass this is a macro-averaged // metric treating each class as a binary classifier. Precision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=precision,proto3" json:"precision,omitempty"` // Recall is the fraction of actual positive labels that were given a // positive prediction. For multiclass this is a macro-averaged metric. Recall *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=recall,proto3" json:"recall,omitempty"` // Accuracy is the fraction of predictions given the correct label. For // multiclass this is a micro-averaged metric. Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=accuracy,proto3" json:"accuracy,omitempty"` // Threshold at which the metrics are computed. For binary // classification models this is the positive class threshold. // For multi-class classfication models this is the confidence // threshold. Threshold *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=threshold,proto3" json:"threshold,omitempty"` // The F1 score is an average of recall and precision. For multiclass // this is a macro-averaged metric. F1Score *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"` // Logarithmic Loss. For multiclass this is a macro-averaged metric. LogLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=log_loss,json=logLoss,proto3" json:"log_loss,omitempty"` // Area Under a ROC Curve. For multiclass this is a macro-averaged // metric. RocAuc *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=roc_auc,json=rocAuc,proto3" json:"roc_auc,omitempty"` // contains filtered or unexported fields }
Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.
func (*Model_AggregateClassificationMetrics) Descriptor
deprecated
func (*Model_AggregateClassificationMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_AggregateClassificationMetrics.ProtoReflect.Descriptor instead.
func (*Model_AggregateClassificationMetrics) GetAccuracy ¶
func (x *Model_AggregateClassificationMetrics) GetAccuracy() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetF1Score ¶
func (x *Model_AggregateClassificationMetrics) GetF1Score() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetLogLoss ¶
func (x *Model_AggregateClassificationMetrics) GetLogLoss() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetPrecision ¶
func (x *Model_AggregateClassificationMetrics) GetPrecision() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetRecall ¶
func (x *Model_AggregateClassificationMetrics) GetRecall() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetRocAuc ¶
func (x *Model_AggregateClassificationMetrics) GetRocAuc() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) GetThreshold ¶
func (x *Model_AggregateClassificationMetrics) GetThreshold() *wrapperspb.DoubleValue
func (*Model_AggregateClassificationMetrics) ProtoMessage ¶
func (*Model_AggregateClassificationMetrics) ProtoMessage()
func (*Model_AggregateClassificationMetrics) ProtoReflect ¶
func (x *Model_AggregateClassificationMetrics) ProtoReflect() protoreflect.Message
func (*Model_AggregateClassificationMetrics) Reset ¶
func (x *Model_AggregateClassificationMetrics) Reset()
func (*Model_AggregateClassificationMetrics) String ¶
func (x *Model_AggregateClassificationMetrics) String() string
type Model_ArimaFittingMetrics ¶
type Model_ArimaFittingMetrics struct { // Log-likelihood. LogLikelihood float64 `protobuf:"fixed64,1,opt,name=log_likelihood,json=logLikelihood,proto3" json:"log_likelihood,omitempty"` // AIC. Aic float64 `protobuf:"fixed64,2,opt,name=aic,proto3" json:"aic,omitempty"` // Variance. Variance float64 `protobuf:"fixed64,3,opt,name=variance,proto3" json:"variance,omitempty"` // contains filtered or unexported fields }
ARIMA model fitting metrics.
func (*Model_ArimaFittingMetrics) Descriptor
deprecated
func (*Model_ArimaFittingMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_ArimaFittingMetrics.ProtoReflect.Descriptor instead.
func (*Model_ArimaFittingMetrics) GetAic ¶
func (x *Model_ArimaFittingMetrics) GetAic() float64
func (*Model_ArimaFittingMetrics) GetLogLikelihood ¶
func (x *Model_ArimaFittingMetrics) GetLogLikelihood() float64
func (*Model_ArimaFittingMetrics) GetVariance ¶
func (x *Model_ArimaFittingMetrics) GetVariance() float64
func (*Model_ArimaFittingMetrics) ProtoMessage ¶
func (*Model_ArimaFittingMetrics) ProtoMessage()
func (*Model_ArimaFittingMetrics) ProtoReflect ¶
func (x *Model_ArimaFittingMetrics) ProtoReflect() protoreflect.Message
func (*Model_ArimaFittingMetrics) Reset ¶
func (x *Model_ArimaFittingMetrics) Reset()
func (*Model_ArimaFittingMetrics) String ¶
func (x *Model_ArimaFittingMetrics) String() string
type Model_ArimaForecastingMetrics ¶
type Model_ArimaForecastingMetrics struct { // Non-seasonal order. NonSeasonalOrder []*Model_ArimaOrder `protobuf:"bytes,1,rep,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"` // Arima model fitting metrics. ArimaFittingMetrics []*Model_ArimaFittingMetrics `protobuf:"bytes,2,rep,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"` // Seasonal periods. Repeated because multiple periods are supported for one // time series. SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `` /* 184-byte string literal not displayed */ // Whether Arima model fitted with drift or not. It is always false when d // is not 1. HasDrift []bool `protobuf:"varint,4,rep,packed,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"` // Id to differentiate different time series for the large-scale case. TimeSeriesId []string `protobuf:"bytes,5,rep,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"` // Repeated as there can be many metric sets (one for each model) in // auto-arima and the large-scale case. ArimaSingleModelForecastingMetrics []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics `` /* 169-byte string literal not displayed */ // contains filtered or unexported fields }
Model evaluation metrics for ARIMA forecasting models.
func (*Model_ArimaForecastingMetrics) Descriptor
deprecated
func (*Model_ArimaForecastingMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_ArimaForecastingMetrics.ProtoReflect.Descriptor instead.
func (*Model_ArimaForecastingMetrics) GetArimaFittingMetrics ¶
func (x *Model_ArimaForecastingMetrics) GetArimaFittingMetrics() []*Model_ArimaFittingMetrics
func (*Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics ¶
func (x *Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics() []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics
func (*Model_ArimaForecastingMetrics) GetHasDrift ¶
func (x *Model_ArimaForecastingMetrics) GetHasDrift() []bool
func (*Model_ArimaForecastingMetrics) GetNonSeasonalOrder ¶
func (x *Model_ArimaForecastingMetrics) GetNonSeasonalOrder() []*Model_ArimaOrder
func (*Model_ArimaForecastingMetrics) GetSeasonalPeriods ¶
func (x *Model_ArimaForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
func (*Model_ArimaForecastingMetrics) GetTimeSeriesId ¶
func (x *Model_ArimaForecastingMetrics) GetTimeSeriesId() []string
func (*Model_ArimaForecastingMetrics) ProtoMessage ¶
func (*Model_ArimaForecastingMetrics) ProtoMessage()
func (*Model_ArimaForecastingMetrics) ProtoReflect ¶
func (x *Model_ArimaForecastingMetrics) ProtoReflect() protoreflect.Message
func (*Model_ArimaForecastingMetrics) Reset ¶
func (x *Model_ArimaForecastingMetrics) Reset()
func (*Model_ArimaForecastingMetrics) String ¶
func (x *Model_ArimaForecastingMetrics) String() string
type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics ¶
type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics struct { // Non-seasonal order. NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"` // Arima fitting metrics. ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,2,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"` // Is arima model fitted with drift or not. It is always false when d // is not 1. HasDrift bool `protobuf:"varint,3,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"` // The id to indicate different time series. TimeSeriesId string `protobuf:"bytes,4,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"` // Seasonal periods. Repeated because multiple periods are supported // for one time series. SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `` /* 184-byte string literal not displayed */ // contains filtered or unexported fields }
Model evaluation metrics for a single ARIMA forecasting model.
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor
deprecated
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics.ProtoReflect.Descriptor instead.
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics() *Model_ArimaFittingMetrics
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift() bool
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder() *Model_ArimaOrder
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId() string
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage ¶
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage()
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect() protoreflect.Message
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset()
func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String ¶
func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String() string
type Model_ArimaOrder ¶
type Model_ArimaOrder struct { // Order of the autoregressive part. P int64 `protobuf:"varint,1,opt,name=p,proto3" json:"p,omitempty"` // Order of the differencing part. D int64 `protobuf:"varint,2,opt,name=d,proto3" json:"d,omitempty"` // Order of the moving-average part. Q int64 `protobuf:"varint,3,opt,name=q,proto3" json:"q,omitempty"` // contains filtered or unexported fields }
Arima order, can be used for both non-seasonal and seasonal parts.
func (*Model_ArimaOrder) Descriptor
deprecated
func (*Model_ArimaOrder) Descriptor() ([]byte, []int)
Deprecated: Use Model_ArimaOrder.ProtoReflect.Descriptor instead.
func (*Model_ArimaOrder) GetD ¶
func (x *Model_ArimaOrder) GetD() int64
func (*Model_ArimaOrder) GetP ¶
func (x *Model_ArimaOrder) GetP() int64
func (*Model_ArimaOrder) GetQ ¶
func (x *Model_ArimaOrder) GetQ() int64
func (*Model_ArimaOrder) ProtoMessage ¶
func (*Model_ArimaOrder) ProtoMessage()
func (*Model_ArimaOrder) ProtoReflect ¶
func (x *Model_ArimaOrder) ProtoReflect() protoreflect.Message
func (*Model_ArimaOrder) Reset ¶
func (x *Model_ArimaOrder) Reset()
func (*Model_ArimaOrder) String ¶
func (x *Model_ArimaOrder) String() string
type Model_BinaryClassificationMetrics ¶
type Model_BinaryClassificationMetrics struct { // Aggregate classification metrics. AggregateClassificationMetrics *Model_AggregateClassificationMetrics `` /* 153-byte string literal not displayed */ // Binary confusion matrix at multiple thresholds. BinaryConfusionMatrixList []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix `` /* 140-byte string literal not displayed */ // Label representing the positive class. PositiveLabel string `protobuf:"bytes,3,opt,name=positive_label,json=positiveLabel,proto3" json:"positive_label,omitempty"` // Label representing the negative class. NegativeLabel string `protobuf:"bytes,4,opt,name=negative_label,json=negativeLabel,proto3" json:"negative_label,omitempty"` // contains filtered or unexported fields }
Evaluation metrics for binary classification/classifier models.
func (*Model_BinaryClassificationMetrics) Descriptor
deprecated
func (*Model_BinaryClassificationMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_BinaryClassificationMetrics.ProtoReflect.Descriptor instead.
func (*Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics ¶
func (x *Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics
func (*Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList ¶
func (x *Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList() []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix
func (*Model_BinaryClassificationMetrics) GetNegativeLabel ¶
func (x *Model_BinaryClassificationMetrics) GetNegativeLabel() string
func (*Model_BinaryClassificationMetrics) GetPositiveLabel ¶
func (x *Model_BinaryClassificationMetrics) GetPositiveLabel() string
func (*Model_BinaryClassificationMetrics) ProtoMessage ¶
func (*Model_BinaryClassificationMetrics) ProtoMessage()
func (*Model_BinaryClassificationMetrics) ProtoReflect ¶
func (x *Model_BinaryClassificationMetrics) ProtoReflect() protoreflect.Message
func (*Model_BinaryClassificationMetrics) Reset ¶
func (x *Model_BinaryClassificationMetrics) Reset()
func (*Model_BinaryClassificationMetrics) String ¶
func (x *Model_BinaryClassificationMetrics) String() string
type Model_BinaryClassificationMetrics_BinaryConfusionMatrix ¶
type Model_BinaryClassificationMetrics_BinaryConfusionMatrix struct { // Threshold value used when computing each of the following metric. PositiveClassThreshold *wrapperspb.DoubleValue `` /* 129-byte string literal not displayed */ // Number of true samples predicted as true. TruePositives *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=true_positives,json=truePositives,proto3" json:"true_positives,omitempty"` // Number of false samples predicted as true. FalsePositives *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=false_positives,json=falsePositives,proto3" json:"false_positives,omitempty"` // Number of true samples predicted as false. TrueNegatives *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=true_negatives,json=trueNegatives,proto3" json:"true_negatives,omitempty"` // Number of false samples predicted as false. FalseNegatives *wrapperspb.Int64Value `protobuf:"bytes,5,opt,name=false_negatives,json=falseNegatives,proto3" json:"false_negatives,omitempty"` // The fraction of actual positive predictions that had positive actual // labels. Precision *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=precision,proto3" json:"precision,omitempty"` // The fraction of actual positive labels that were given a positive // prediction. Recall *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=recall,proto3" json:"recall,omitempty"` // The equally weighted average of recall and precision. F1Score *wrapperspb.DoubleValue `protobuf:"bytes,8,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"` // The fraction of predictions given the correct label. Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,9,opt,name=accuracy,proto3" json:"accuracy,omitempty"` // contains filtered or unexported fields }
Confusion matrix for binary classification models.
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor
deprecated
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor() ([]byte, []int)
Deprecated: Use Model_BinaryClassificationMetrics_BinaryConfusionMatrix.ProtoReflect.Descriptor instead.
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy() *wrapperspb.DoubleValue
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score() *wrapperspb.DoubleValue
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives() *wrapperspb.Int64Value
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives() *wrapperspb.Int64Value
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold() *wrapperspb.DoubleValue
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision() *wrapperspb.DoubleValue
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall() *wrapperspb.DoubleValue
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives() *wrapperspb.Int64Value
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives() *wrapperspb.Int64Value
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage ¶
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage()
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect() protoreflect.Message
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset()
func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String ¶
func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String() string
type Model_ClusteringMetrics ¶
type Model_ClusteringMetrics struct { // Davies-Bouldin index. DaviesBouldinIndex *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=davies_bouldin_index,json=daviesBouldinIndex,proto3" json:"davies_bouldin_index,omitempty"` // Mean of squared distances between each sample to its cluster centroid. MeanSquaredDistance *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_distance,json=meanSquaredDistance,proto3" json:"mean_squared_distance,omitempty"` // [Beta] Information for all clusters. Clusters []*Model_ClusteringMetrics_Cluster `protobuf:"bytes,3,rep,name=clusters,proto3" json:"clusters,omitempty"` // contains filtered or unexported fields }
Evaluation metrics for clustering models.
func (*Model_ClusteringMetrics) Descriptor
deprecated
func (*Model_ClusteringMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_ClusteringMetrics.ProtoReflect.Descriptor instead.
func (*Model_ClusteringMetrics) GetClusters ¶
func (x *Model_ClusteringMetrics) GetClusters() []*Model_ClusteringMetrics_Cluster
func (*Model_ClusteringMetrics) GetDaviesBouldinIndex ¶
func (x *Model_ClusteringMetrics) GetDaviesBouldinIndex() *wrapperspb.DoubleValue
func (*Model_ClusteringMetrics) GetMeanSquaredDistance ¶
func (x *Model_ClusteringMetrics) GetMeanSquaredDistance() *wrapperspb.DoubleValue
func (*Model_ClusteringMetrics) ProtoMessage ¶
func (*Model_ClusteringMetrics) ProtoMessage()
func (*Model_ClusteringMetrics) ProtoReflect ¶
func (x *Model_ClusteringMetrics) ProtoReflect() protoreflect.Message
func (*Model_ClusteringMetrics) Reset ¶
func (x *Model_ClusteringMetrics) Reset()
func (*Model_ClusteringMetrics) String ¶
func (x *Model_ClusteringMetrics) String() string
type Model_ClusteringMetrics_Cluster ¶
type Model_ClusteringMetrics_Cluster struct { // Centroid id. CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"` // Values of highly variant features for this cluster. FeatureValues []*Model_ClusteringMetrics_Cluster_FeatureValue `protobuf:"bytes,2,rep,name=feature_values,json=featureValues,proto3" json:"feature_values,omitempty"` // Count of training data rows that were assigned to this cluster. Count *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=count,proto3" json:"count,omitempty"` // contains filtered or unexported fields }
Message containing the information about one cluster.
func (*Model_ClusteringMetrics_Cluster) Descriptor
deprecated
func (*Model_ClusteringMetrics_Cluster) Descriptor() ([]byte, []int)
Deprecated: Use Model_ClusteringMetrics_Cluster.ProtoReflect.Descriptor instead.
func (*Model_ClusteringMetrics_Cluster) GetCentroidId ¶
func (x *Model_ClusteringMetrics_Cluster) GetCentroidId() int64
func (*Model_ClusteringMetrics_Cluster) GetCount ¶
func (x *Model_ClusteringMetrics_Cluster) GetCount() *wrapperspb.Int64Value
func (*Model_ClusteringMetrics_Cluster) GetFeatureValues ¶
func (x *Model_ClusteringMetrics_Cluster) GetFeatureValues() []*Model_ClusteringMetrics_Cluster_FeatureValue
func (*Model_ClusteringMetrics_Cluster) ProtoMessage ¶
func (*Model_ClusteringMetrics_Cluster) ProtoMessage()
func (*Model_ClusteringMetrics_Cluster) ProtoReflect ¶
func (x *Model_ClusteringMetrics_Cluster) ProtoReflect() protoreflect.Message
func (*Model_ClusteringMetrics_Cluster) Reset ¶
func (x *Model_ClusteringMetrics_Cluster) Reset()
func (*Model_ClusteringMetrics_Cluster) String ¶
func (x *Model_ClusteringMetrics_Cluster) String() string
type Model_ClusteringMetrics_Cluster_FeatureValue ¶
type Model_ClusteringMetrics_Cluster_FeatureValue struct { // The feature column name. FeatureColumn string `protobuf:"bytes,1,opt,name=feature_column,json=featureColumn,proto3" json:"feature_column,omitempty"` // Types that are assignable to Value: // *Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue // *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ Value isModel_ClusteringMetrics_Cluster_FeatureValue_Value `protobuf_oneof:"value"` // contains filtered or unexported fields }
Representative value of a single feature within the cluster.
func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor
deprecated
func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor() ([]byte, []int)
Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue.ProtoReflect.Descriptor instead.
func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue() *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue
func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn() string
func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue() *wrapperspb.DoubleValue
func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetValue ¶
func (m *Model_ClusteringMetrics_Cluster_FeatureValue) GetValue() isModel_ClusteringMetrics_Cluster_FeatureValue_Value
func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage ¶
func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage()
func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect() protoreflect.Message
func (*Model_ClusteringMetrics_Cluster_FeatureValue) Reset ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) Reset()
func (*Model_ClusteringMetrics_Cluster_FeatureValue) String ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue) String() string
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue ¶
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue struct { // Counts of all categories for the categorical feature. If there are // more than ten categories, we return top ten (by count) and return // one more CategoryCount with category "_OTHER_" and count as // aggregate counts of remaining categories. CategoryCounts []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount `protobuf:"bytes,1,rep,name=category_counts,json=categoryCounts,proto3" json:"category_counts,omitempty"` // contains filtered or unexported fields }
Representative value of a categorical feature.
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor
deprecated
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor() ([]byte, []int)
Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue.ProtoReflect.Descriptor instead.
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts() []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage ¶
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage()
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect() protoreflect.Message
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset()
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String() string
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ ¶
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ struct { // The categorical feature value. CategoricalValue *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue `protobuf:"bytes,3,opt,name=categorical_value,json=categoricalValue,proto3,oneof"` }
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount ¶
type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount struct { // The name of category. Category string `protobuf:"bytes,1,opt,name=category,proto3" json:"category,omitempty"` // The count of training samples matching the category within the // cluster. Count *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=count,proto3" json:"count,omitempty"` // contains filtered or unexported fields }
Represents the count of a single category within the cluster.
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor
deprecated
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor() ([]byte, []int)
Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount.ProtoReflect.Descriptor instead.
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory() string
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount() *wrapperspb.Int64Value
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage ¶
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage()
func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect ¶
func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect() protoreflect.Message
type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue ¶
type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue struct { // The numerical feature value. This is the centroid value for this // feature. NumericalValue *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=numerical_value,json=numericalValue,proto3,oneof"` }
type Model_DataFrequency ¶
type Model_DataFrequency int32
Type of supported data frequency for time series forecasting models.
const ( Model_DATA_FREQUENCY_UNSPECIFIED Model_DataFrequency = 0 // Automatically inferred from timestamps. Model_AUTO_FREQUENCY Model_DataFrequency = 1 // Yearly data. Model_YEARLY Model_DataFrequency = 2 // Quarterly data. Model_QUARTERLY Model_DataFrequency = 3 // Monthly data. Model_MONTHLY Model_DataFrequency = 4 // Weekly data. Model_WEEKLY Model_DataFrequency = 5 // Daily data. Model_DAILY Model_DataFrequency = 6 // Hourly data. Model_HOURLY Model_DataFrequency = 7 )
func (Model_DataFrequency) Descriptor ¶
func (Model_DataFrequency) Descriptor() protoreflect.EnumDescriptor
func (Model_DataFrequency) Enum ¶
func (x Model_DataFrequency) Enum() *Model_DataFrequency
func (Model_DataFrequency) EnumDescriptor
deprecated
func (Model_DataFrequency) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_DataFrequency.Descriptor instead.
func (Model_DataFrequency) Number ¶
func (x Model_DataFrequency) Number() protoreflect.EnumNumber
func (Model_DataFrequency) String ¶
func (x Model_DataFrequency) String() string
func (Model_DataFrequency) Type ¶
func (Model_DataFrequency) Type() protoreflect.EnumType
type Model_DataSplitMethod ¶
type Model_DataSplitMethod int32
Indicates the method to split input data into multiple tables.
const ( Model_DATA_SPLIT_METHOD_UNSPECIFIED Model_DataSplitMethod = 0 // Splits data randomly. Model_RANDOM Model_DataSplitMethod = 1 // Splits data with the user provided tags. Model_CUSTOM Model_DataSplitMethod = 2 // Splits data sequentially. Model_SEQUENTIAL Model_DataSplitMethod = 3 // Data split will be skipped. Model_NO_SPLIT Model_DataSplitMethod = 4 // Splits data automatically: Uses NO_SPLIT if the data size is small. // Otherwise uses RANDOM. Model_AUTO_SPLIT Model_DataSplitMethod = 5 )
func (Model_DataSplitMethod) Descriptor ¶
func (Model_DataSplitMethod) Descriptor() protoreflect.EnumDescriptor
func (Model_DataSplitMethod) Enum ¶
func (x Model_DataSplitMethod) Enum() *Model_DataSplitMethod
func (Model_DataSplitMethod) EnumDescriptor
deprecated
func (Model_DataSplitMethod) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_DataSplitMethod.Descriptor instead.
func (Model_DataSplitMethod) Number ¶
func (x Model_DataSplitMethod) Number() protoreflect.EnumNumber
func (Model_DataSplitMethod) String ¶
func (x Model_DataSplitMethod) String() string
func (Model_DataSplitMethod) Type ¶
func (Model_DataSplitMethod) Type() protoreflect.EnumType
type Model_DataSplitResult ¶
type Model_DataSplitResult struct { // Table reference of the training data after split. TrainingTable *TableReference `protobuf:"bytes,1,opt,name=training_table,json=trainingTable,proto3" json:"training_table,omitempty"` // Table reference of the evaluation data after split. EvaluationTable *TableReference `protobuf:"bytes,2,opt,name=evaluation_table,json=evaluationTable,proto3" json:"evaluation_table,omitempty"` // contains filtered or unexported fields }
Data split result. This contains references to the training and evaluation data tables that were used to train the model.
func (*Model_DataSplitResult) Descriptor
deprecated
func (*Model_DataSplitResult) Descriptor() ([]byte, []int)
Deprecated: Use Model_DataSplitResult.ProtoReflect.Descriptor instead.
func (*Model_DataSplitResult) GetEvaluationTable ¶
func (x *Model_DataSplitResult) GetEvaluationTable() *TableReference
func (*Model_DataSplitResult) GetTrainingTable ¶
func (x *Model_DataSplitResult) GetTrainingTable() *TableReference
func (*Model_DataSplitResult) ProtoMessage ¶
func (*Model_DataSplitResult) ProtoMessage()
func (*Model_DataSplitResult) ProtoReflect ¶
func (x *Model_DataSplitResult) ProtoReflect() protoreflect.Message
func (*Model_DataSplitResult) Reset ¶
func (x *Model_DataSplitResult) Reset()
func (*Model_DataSplitResult) String ¶
func (x *Model_DataSplitResult) String() string
type Model_DistanceType ¶
type Model_DistanceType int32
Distance metric used to compute the distance between two points.
const ( Model_DISTANCE_TYPE_UNSPECIFIED Model_DistanceType = 0 // Eculidean distance. Model_EUCLIDEAN Model_DistanceType = 1 // Cosine distance. Model_COSINE Model_DistanceType = 2 )
func (Model_DistanceType) Descriptor ¶
func (Model_DistanceType) Descriptor() protoreflect.EnumDescriptor
func (Model_DistanceType) Enum ¶
func (x Model_DistanceType) Enum() *Model_DistanceType
func (Model_DistanceType) EnumDescriptor
deprecated
func (Model_DistanceType) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_DistanceType.Descriptor instead.
func (Model_DistanceType) Number ¶
func (x Model_DistanceType) Number() protoreflect.EnumNumber
func (Model_DistanceType) String ¶
func (x Model_DistanceType) String() string
func (Model_DistanceType) Type ¶
func (Model_DistanceType) Type() protoreflect.EnumType
type Model_EvaluationMetrics ¶
type Model_EvaluationMetrics struct { // Types that are assignable to Metrics: // *Model_EvaluationMetrics_RegressionMetrics // *Model_EvaluationMetrics_BinaryClassificationMetrics // *Model_EvaluationMetrics_MultiClassClassificationMetrics // *Model_EvaluationMetrics_ClusteringMetrics // *Model_EvaluationMetrics_RankingMetrics // *Model_EvaluationMetrics_ArimaForecastingMetrics Metrics isModel_EvaluationMetrics_Metrics `protobuf_oneof:"metrics"` // contains filtered or unexported fields }
Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.
func (*Model_EvaluationMetrics) Descriptor
deprecated
func (*Model_EvaluationMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_EvaluationMetrics.ProtoReflect.Descriptor instead.
func (*Model_EvaluationMetrics) GetArimaForecastingMetrics ¶
func (x *Model_EvaluationMetrics) GetArimaForecastingMetrics() *Model_ArimaForecastingMetrics
func (*Model_EvaluationMetrics) GetBinaryClassificationMetrics ¶
func (x *Model_EvaluationMetrics) GetBinaryClassificationMetrics() *Model_BinaryClassificationMetrics
func (*Model_EvaluationMetrics) GetClusteringMetrics ¶
func (x *Model_EvaluationMetrics) GetClusteringMetrics() *Model_ClusteringMetrics
func (*Model_EvaluationMetrics) GetMetrics ¶
func (m *Model_EvaluationMetrics) GetMetrics() isModel_EvaluationMetrics_Metrics
func (*Model_EvaluationMetrics) GetMultiClassClassificationMetrics ¶
func (x *Model_EvaluationMetrics) GetMultiClassClassificationMetrics() *Model_MultiClassClassificationMetrics
func (*Model_EvaluationMetrics) GetRankingMetrics ¶
func (x *Model_EvaluationMetrics) GetRankingMetrics() *Model_RankingMetrics
func (*Model_EvaluationMetrics) GetRegressionMetrics ¶
func (x *Model_EvaluationMetrics) GetRegressionMetrics() *Model_RegressionMetrics
func (*Model_EvaluationMetrics) ProtoMessage ¶
func (*Model_EvaluationMetrics) ProtoMessage()
func (*Model_EvaluationMetrics) ProtoReflect ¶
func (x *Model_EvaluationMetrics) ProtoReflect() protoreflect.Message
func (*Model_EvaluationMetrics) Reset ¶
func (x *Model_EvaluationMetrics) Reset()
func (*Model_EvaluationMetrics) String ¶
func (x *Model_EvaluationMetrics) String() string
type Model_EvaluationMetrics_ArimaForecastingMetrics ¶
type Model_EvaluationMetrics_ArimaForecastingMetrics struct { // Populated for ARIMA models. ArimaForecastingMetrics *Model_ArimaForecastingMetrics `protobuf:"bytes,6,opt,name=arima_forecasting_metrics,json=arimaForecastingMetrics,proto3,oneof"` }
type Model_EvaluationMetrics_BinaryClassificationMetrics ¶
type Model_EvaluationMetrics_BinaryClassificationMetrics struct { // Populated for binary classification/classifier models. BinaryClassificationMetrics *Model_BinaryClassificationMetrics `protobuf:"bytes,2,opt,name=binary_classification_metrics,json=binaryClassificationMetrics,proto3,oneof"` }
type Model_EvaluationMetrics_ClusteringMetrics ¶
type Model_EvaluationMetrics_ClusteringMetrics struct { // Populated for clustering models. ClusteringMetrics *Model_ClusteringMetrics `protobuf:"bytes,4,opt,name=clustering_metrics,json=clusteringMetrics,proto3,oneof"` }
type Model_EvaluationMetrics_MultiClassClassificationMetrics ¶
type Model_EvaluationMetrics_MultiClassClassificationMetrics struct { // Populated for multi-class classification/classifier models. MultiClassClassificationMetrics *Model_MultiClassClassificationMetrics `protobuf:"bytes,3,opt,name=multi_class_classification_metrics,json=multiClassClassificationMetrics,proto3,oneof"` }
type Model_EvaluationMetrics_RankingMetrics ¶
type Model_EvaluationMetrics_RankingMetrics struct { // Populated for implicit feedback type matrix factorization models. RankingMetrics *Model_RankingMetrics `protobuf:"bytes,5,opt,name=ranking_metrics,json=rankingMetrics,proto3,oneof"` }
type Model_EvaluationMetrics_RegressionMetrics ¶
type Model_EvaluationMetrics_RegressionMetrics struct { // Populated for regression models and explicit feedback type matrix // factorization models. RegressionMetrics *Model_RegressionMetrics `protobuf:"bytes,1,opt,name=regression_metrics,json=regressionMetrics,proto3,oneof"` }
type Model_FeedbackType ¶
type Model_FeedbackType int32
Indicates the training algorithm to use for matrix factorization models.
const ( Model_FEEDBACK_TYPE_UNSPECIFIED Model_FeedbackType = 0 // Use weighted-als for implicit feedback problems. Model_IMPLICIT Model_FeedbackType = 1 // Use nonweighted-als for explicit feedback problems. Model_EXPLICIT Model_FeedbackType = 2 )
func (Model_FeedbackType) Descriptor ¶
func (Model_FeedbackType) Descriptor() protoreflect.EnumDescriptor
func (Model_FeedbackType) Enum ¶
func (x Model_FeedbackType) Enum() *Model_FeedbackType
func (Model_FeedbackType) EnumDescriptor
deprecated
func (Model_FeedbackType) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_FeedbackType.Descriptor instead.
func (Model_FeedbackType) Number ¶
func (x Model_FeedbackType) Number() protoreflect.EnumNumber
func (Model_FeedbackType) String ¶
func (x Model_FeedbackType) String() string
func (Model_FeedbackType) Type ¶
func (Model_FeedbackType) Type() protoreflect.EnumType
type Model_GlobalExplanation ¶
type Model_GlobalExplanation struct { // A list of the top global explanations. Sorted by absolute value of // attribution in descending order. Explanations []*Model_GlobalExplanation_Explanation `protobuf:"bytes,1,rep,name=explanations,proto3" json:"explanations,omitempty"` // Class label for this set of global explanations. Will be empty/null for // binary logistic and linear regression models. Sorted alphabetically in // descending order. ClassLabel string `protobuf:"bytes,2,opt,name=class_label,json=classLabel,proto3" json:"class_label,omitempty"` // contains filtered or unexported fields }
Global explanations containing the top most important features after training.
func (*Model_GlobalExplanation) Descriptor
deprecated
func (*Model_GlobalExplanation) Descriptor() ([]byte, []int)
Deprecated: Use Model_GlobalExplanation.ProtoReflect.Descriptor instead.
func (*Model_GlobalExplanation) GetClassLabel ¶
func (x *Model_GlobalExplanation) GetClassLabel() string
func (*Model_GlobalExplanation) GetExplanations ¶
func (x *Model_GlobalExplanation) GetExplanations() []*Model_GlobalExplanation_Explanation
func (*Model_GlobalExplanation) ProtoMessage ¶
func (*Model_GlobalExplanation) ProtoMessage()
func (*Model_GlobalExplanation) ProtoReflect ¶
func (x *Model_GlobalExplanation) ProtoReflect() protoreflect.Message
func (*Model_GlobalExplanation) Reset ¶
func (x *Model_GlobalExplanation) Reset()
func (*Model_GlobalExplanation) String ¶
func (x *Model_GlobalExplanation) String() string
type Model_GlobalExplanation_Explanation ¶
type Model_GlobalExplanation_Explanation struct { // Full name of the feature. For non-numerical features, will be // formatted like <column_name>.<encoded_feature_name>. Overall size of // feature name will always be truncated to first 120 characters. FeatureName string `protobuf:"bytes,1,opt,name=feature_name,json=featureName,proto3" json:"feature_name,omitempty"` // Attribution of feature. Attribution *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=attribution,proto3" json:"attribution,omitempty"` // contains filtered or unexported fields }
Explanation for a single feature.
func (*Model_GlobalExplanation_Explanation) Descriptor
deprecated
func (*Model_GlobalExplanation_Explanation) Descriptor() ([]byte, []int)
Deprecated: Use Model_GlobalExplanation_Explanation.ProtoReflect.Descriptor instead.
func (*Model_GlobalExplanation_Explanation) GetAttribution ¶
func (x *Model_GlobalExplanation_Explanation) GetAttribution() *wrapperspb.DoubleValue
func (*Model_GlobalExplanation_Explanation) GetFeatureName ¶
func (x *Model_GlobalExplanation_Explanation) GetFeatureName() string
func (*Model_GlobalExplanation_Explanation) ProtoMessage ¶
func (*Model_GlobalExplanation_Explanation) ProtoMessage()
func (*Model_GlobalExplanation_Explanation) ProtoReflect ¶
func (x *Model_GlobalExplanation_Explanation) ProtoReflect() protoreflect.Message
func (*Model_GlobalExplanation_Explanation) Reset ¶
func (x *Model_GlobalExplanation_Explanation) Reset()
func (*Model_GlobalExplanation_Explanation) String ¶
func (x *Model_GlobalExplanation_Explanation) String() string
type Model_HolidayRegion ¶
type Model_HolidayRegion int32
Type of supported holiday regions for time series forecasting models.
const ( // Holiday region unspecified. Model_HOLIDAY_REGION_UNSPECIFIED Model_HolidayRegion = 0 // Global. Model_GLOBAL Model_HolidayRegion = 1 // North America. Model_NA Model_HolidayRegion = 2 // Japan and Asia Pacific: Korea, Greater China, India, Australia, and New // Zealand. Model_JAPAC Model_HolidayRegion = 3 // Europe, the Middle East and Africa. Model_EMEA Model_HolidayRegion = 4 // Latin America and the Caribbean. Model_LAC Model_HolidayRegion = 5 // United Arab Emirates Model_AE Model_HolidayRegion = 6 // Argentina Model_AR Model_HolidayRegion = 7 // Austria Model_AT Model_HolidayRegion = 8 // Australia Model_AU Model_HolidayRegion = 9 // Belgium Model_BE Model_HolidayRegion = 10 // Brazil Model_BR Model_HolidayRegion = 11 // Canada Model_CA Model_HolidayRegion = 12 // Switzerland Model_CH Model_HolidayRegion = 13 // Chile Model_CL Model_HolidayRegion = 14 // China Model_CN Model_HolidayRegion = 15 // Colombia Model_CO Model_HolidayRegion = 16 // Czechoslovakia Model_CS Model_HolidayRegion = 17 // Czech Republic Model_CZ Model_HolidayRegion = 18 // Germany Model_DE Model_HolidayRegion = 19 // Denmark Model_DK Model_HolidayRegion = 20 // Algeria Model_DZ Model_HolidayRegion = 21 // Ecuador Model_EC Model_HolidayRegion = 22 // Estonia Model_EE Model_HolidayRegion = 23 // Egypt Model_EG Model_HolidayRegion = 24 // Spain Model_ES Model_HolidayRegion = 25 // Finland Model_FI Model_HolidayRegion = 26 // France Model_FR Model_HolidayRegion = 27 // Great Britain (United Kingdom) Model_GB Model_HolidayRegion = 28 // Greece Model_GR Model_HolidayRegion = 29 // Hong Kong Model_HK Model_HolidayRegion = 30 // Hungary Model_HU Model_HolidayRegion = 31 // Indonesia Model_ID Model_HolidayRegion = 32 // Ireland Model_IE Model_HolidayRegion = 33 // Israel Model_IL Model_HolidayRegion = 34 // India Model_IN Model_HolidayRegion = 35 // Iran Model_IR Model_HolidayRegion = 36 // Italy Model_IT Model_HolidayRegion = 37 // Japan Model_JP Model_HolidayRegion = 38 // Korea (South) Model_KR Model_HolidayRegion = 39 // Latvia Model_LV Model_HolidayRegion = 40 // Morocco Model_MA Model_HolidayRegion = 41 // Mexico Model_MX Model_HolidayRegion = 42 // Malaysia Model_MY Model_HolidayRegion = 43 // Nigeria Model_NG Model_HolidayRegion = 44 // Netherlands Model_NL Model_HolidayRegion = 45 // Norway Model_NO Model_HolidayRegion = 46 // New Zealand Model_NZ Model_HolidayRegion = 47 // Peru Model_PE Model_HolidayRegion = 48 // Philippines Model_PH Model_HolidayRegion = 49 // Pakistan Model_PK Model_HolidayRegion = 50 // Poland Model_PL Model_HolidayRegion = 51 // Portugal Model_PT Model_HolidayRegion = 52 // Romania Model_RO Model_HolidayRegion = 53 // Serbia Model_RS Model_HolidayRegion = 54 // Russian Federation Model_RU Model_HolidayRegion = 55 // Saudi Arabia Model_SA Model_HolidayRegion = 56 // Sweden Model_SE Model_HolidayRegion = 57 // Singapore Model_SG Model_HolidayRegion = 58 // Slovenia Model_SI Model_HolidayRegion = 59 // Slovakia Model_SK Model_HolidayRegion = 60 // Thailand Model_TH Model_HolidayRegion = 61 // Turkey Model_TR Model_HolidayRegion = 62 // Taiwan Model_TW Model_HolidayRegion = 63 // Ukraine Model_UA Model_HolidayRegion = 64 // United States Model_US Model_HolidayRegion = 65 // Venezuela Model_VE Model_HolidayRegion = 66 // Viet Nam Model_VN Model_HolidayRegion = 67 // South Africa Model_ZA Model_HolidayRegion = 68 )
func (Model_HolidayRegion) Descriptor ¶
func (Model_HolidayRegion) Descriptor() protoreflect.EnumDescriptor
func (Model_HolidayRegion) Enum ¶
func (x Model_HolidayRegion) Enum() *Model_HolidayRegion
func (Model_HolidayRegion) EnumDescriptor
deprecated
func (Model_HolidayRegion) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_HolidayRegion.Descriptor instead.
func (Model_HolidayRegion) Number ¶
func (x Model_HolidayRegion) Number() protoreflect.EnumNumber
func (Model_HolidayRegion) String ¶
func (x Model_HolidayRegion) String() string
func (Model_HolidayRegion) Type ¶
func (Model_HolidayRegion) Type() protoreflect.EnumType
type Model_KmeansEnums ¶
type Model_KmeansEnums struct {
// contains filtered or unexported fields
}
func (*Model_KmeansEnums) Descriptor
deprecated
func (*Model_KmeansEnums) Descriptor() ([]byte, []int)
Deprecated: Use Model_KmeansEnums.ProtoReflect.Descriptor instead.
func (*Model_KmeansEnums) ProtoMessage ¶
func (*Model_KmeansEnums) ProtoMessage()
func (*Model_KmeansEnums) ProtoReflect ¶
func (x *Model_KmeansEnums) ProtoReflect() protoreflect.Message
func (*Model_KmeansEnums) Reset ¶
func (x *Model_KmeansEnums) Reset()
func (*Model_KmeansEnums) String ¶
func (x *Model_KmeansEnums) String() string
type Model_KmeansEnums_KmeansInitializationMethod ¶
type Model_KmeansEnums_KmeansInitializationMethod int32
Indicates the method used to initialize the centroids for KMeans clustering algorithm.
const ( Model_KmeansEnums_KMEANS_INITIALIZATION_METHOD_UNSPECIFIED Model_KmeansEnums_KmeansInitializationMethod = 0 // Initializes the centroids randomly. Model_KmeansEnums_RANDOM Model_KmeansEnums_KmeansInitializationMethod = 1 // Initializes the centroids using data specified in // kmeans_initialization_column. Model_KmeansEnums_CUSTOM Model_KmeansEnums_KmeansInitializationMethod = 2 // Initializes with kmeans++. Model_KmeansEnums_KMEANS_PLUS_PLUS Model_KmeansEnums_KmeansInitializationMethod = 3 )
func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor ¶
func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor() protoreflect.EnumDescriptor
func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor
deprecated
func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_KmeansEnums_KmeansInitializationMethod.Descriptor instead.
func (Model_KmeansEnums_KmeansInitializationMethod) Number ¶
func (x Model_KmeansEnums_KmeansInitializationMethod) Number() protoreflect.EnumNumber
func (Model_KmeansEnums_KmeansInitializationMethod) String ¶
func (x Model_KmeansEnums_KmeansInitializationMethod) String() string
func (Model_KmeansEnums_KmeansInitializationMethod) Type ¶
func (Model_KmeansEnums_KmeansInitializationMethod) Type() protoreflect.EnumType
type Model_LearnRateStrategy ¶
type Model_LearnRateStrategy int32
Indicates the learning rate optimization strategy to use.
const ( Model_LEARN_RATE_STRATEGY_UNSPECIFIED Model_LearnRateStrategy = 0 // Use line search to determine learning rate. Model_LINE_SEARCH Model_LearnRateStrategy = 1 // Use a constant learning rate. Model_CONSTANT Model_LearnRateStrategy = 2 )
func (Model_LearnRateStrategy) Descriptor ¶
func (Model_LearnRateStrategy) Descriptor() protoreflect.EnumDescriptor
func (Model_LearnRateStrategy) Enum ¶
func (x Model_LearnRateStrategy) Enum() *Model_LearnRateStrategy
func (Model_LearnRateStrategy) EnumDescriptor
deprecated
func (Model_LearnRateStrategy) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_LearnRateStrategy.Descriptor instead.
func (Model_LearnRateStrategy) Number ¶
func (x Model_LearnRateStrategy) Number() protoreflect.EnumNumber
func (Model_LearnRateStrategy) String ¶
func (x Model_LearnRateStrategy) String() string
func (Model_LearnRateStrategy) Type ¶
func (Model_LearnRateStrategy) Type() protoreflect.EnumType
type Model_LossType ¶
type Model_LossType int32
Loss metric to evaluate model training performance.
const ( Model_LOSS_TYPE_UNSPECIFIED Model_LossType = 0 // Mean squared loss, used for linear regression. Model_MEAN_SQUARED_LOSS Model_LossType = 1 // Mean log loss, used for logistic regression. Model_MEAN_LOG_LOSS Model_LossType = 2 )
func (Model_LossType) Descriptor ¶
func (Model_LossType) Descriptor() protoreflect.EnumDescriptor
func (Model_LossType) Enum ¶
func (x Model_LossType) Enum() *Model_LossType
func (Model_LossType) EnumDescriptor
deprecated
func (Model_LossType) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_LossType.Descriptor instead.
func (Model_LossType) Number ¶
func (x Model_LossType) Number() protoreflect.EnumNumber
func (Model_LossType) String ¶
func (x Model_LossType) String() string
func (Model_LossType) Type ¶
func (Model_LossType) Type() protoreflect.EnumType
type Model_ModelType ¶
type Model_ModelType int32
Indicates the type of the Model.
const ( Model_MODEL_TYPE_UNSPECIFIED Model_ModelType = 0 // Linear regression model. Model_LINEAR_REGRESSION Model_ModelType = 1 // Logistic regression based classification model. Model_LOGISTIC_REGRESSION Model_ModelType = 2 // K-means clustering model. Model_KMEANS Model_ModelType = 3 // Matrix factorization model. Model_MATRIX_FACTORIZATION Model_ModelType = 4 // [Beta] DNN classifier model. Model_DNN_CLASSIFIER Model_ModelType = 5 // [Beta] An imported TensorFlow model. Model_TENSORFLOW Model_ModelType = 6 // [Beta] DNN regressor model. Model_DNN_REGRESSOR Model_ModelType = 7 // [Beta] Boosted tree regressor model. Model_BOOSTED_TREE_REGRESSOR Model_ModelType = 9 // [Beta] Boosted tree classifier model. Model_BOOSTED_TREE_CLASSIFIER Model_ModelType = 10 // [Beta] ARIMA model. Model_ARIMA Model_ModelType = 11 // [Beta] AutoML Tables regression model. Model_AUTOML_REGRESSOR Model_ModelType = 12 // [Beta] AutoML Tables classification model. Model_AUTOML_CLASSIFIER Model_ModelType = 13 )
func (Model_ModelType) Descriptor ¶
func (Model_ModelType) Descriptor() protoreflect.EnumDescriptor
func (Model_ModelType) Enum ¶
func (x Model_ModelType) Enum() *Model_ModelType
func (Model_ModelType) EnumDescriptor
deprecated
func (Model_ModelType) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_ModelType.Descriptor instead.
func (Model_ModelType) Number ¶
func (x Model_ModelType) Number() protoreflect.EnumNumber
func (Model_ModelType) String ¶
func (x Model_ModelType) String() string
func (Model_ModelType) Type ¶
func (Model_ModelType) Type() protoreflect.EnumType
type Model_MultiClassClassificationMetrics ¶
type Model_MultiClassClassificationMetrics struct { // Aggregate classification metrics. AggregateClassificationMetrics *Model_AggregateClassificationMetrics `` /* 153-byte string literal not displayed */ // Confusion matrix at different thresholds. ConfusionMatrixList []*Model_MultiClassClassificationMetrics_ConfusionMatrix `protobuf:"bytes,2,rep,name=confusion_matrix_list,json=confusionMatrixList,proto3" json:"confusion_matrix_list,omitempty"` // contains filtered or unexported fields }
Evaluation metrics for multi-class classification/classifier models.
func (*Model_MultiClassClassificationMetrics) Descriptor
deprecated
func (*Model_MultiClassClassificationMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_MultiClassClassificationMetrics.ProtoReflect.Descriptor instead.
func (*Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics ¶
func (x *Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics
func (*Model_MultiClassClassificationMetrics) GetConfusionMatrixList ¶
func (x *Model_MultiClassClassificationMetrics) GetConfusionMatrixList() []*Model_MultiClassClassificationMetrics_ConfusionMatrix
func (*Model_MultiClassClassificationMetrics) ProtoMessage ¶
func (*Model_MultiClassClassificationMetrics) ProtoMessage()
func (*Model_MultiClassClassificationMetrics) ProtoReflect ¶
func (x *Model_MultiClassClassificationMetrics) ProtoReflect() protoreflect.Message
func (*Model_MultiClassClassificationMetrics) Reset ¶
func (x *Model_MultiClassClassificationMetrics) Reset()
func (*Model_MultiClassClassificationMetrics) String ¶
func (x *Model_MultiClassClassificationMetrics) String() string
type Model_MultiClassClassificationMetrics_ConfusionMatrix ¶
type Model_MultiClassClassificationMetrics_ConfusionMatrix struct { // Confidence threshold used when computing the entries of the // confusion matrix. ConfidenceThreshold *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=confidence_threshold,json=confidenceThreshold,proto3" json:"confidence_threshold,omitempty"` // One row per actual label. Rows []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row `protobuf:"bytes,2,rep,name=rows,proto3" json:"rows,omitempty"` // contains filtered or unexported fields }
Confusion matrix for multi-class classification models.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor
deprecated
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor() ([]byte, []int)
Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix.ProtoReflect.Descriptor instead.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold() *wrapperspb.DoubleValue
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage ¶
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect() protoreflect.Message
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) String ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) String() string
type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry ¶
type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry struct { // The predicted label. For confidence_threshold > 0, we will // also add an entry indicating the number of items under the // confidence threshold. PredictedLabel string `protobuf:"bytes,1,opt,name=predicted_label,json=predictedLabel,proto3" json:"predicted_label,omitempty"` // Number of items being predicted as this label. ItemCount *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=item_count,json=itemCount,proto3" json:"item_count,omitempty"` // contains filtered or unexported fields }
A single entry in the confusion matrix.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor
deprecated
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor() ([]byte, []int)
Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry.ProtoReflect.Descriptor instead.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount() *wrapperspb.Int64Value
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel() string
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage ¶
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect() protoreflect.Message
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String() string
type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row ¶
type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row struct { // The original label of this row. ActualLabel string `protobuf:"bytes,1,opt,name=actual_label,json=actualLabel,proto3" json:"actual_label,omitempty"` // Info describing predicted label distribution. Entries []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry `protobuf:"bytes,2,rep,name=entries,proto3" json:"entries,omitempty"` // contains filtered or unexported fields }
A single row in the confusion matrix.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor
deprecated
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor() ([]byte, []int)
Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Row.ProtoReflect.Descriptor instead.
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel() string
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetEntries ¶
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage ¶
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect() protoreflect.Message
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset()
func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String ¶
func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String() string
type Model_OptimizationStrategy ¶
type Model_OptimizationStrategy int32
Indicates the optimization strategy used for training.
const ( Model_OPTIMIZATION_STRATEGY_UNSPECIFIED Model_OptimizationStrategy = 0 // Uses an iterative batch gradient descent algorithm. Model_BATCH_GRADIENT_DESCENT Model_OptimizationStrategy = 1 // Uses a normal equation to solve linear regression problem. Model_NORMAL_EQUATION Model_OptimizationStrategy = 2 )
func (Model_OptimizationStrategy) Descriptor ¶
func (Model_OptimizationStrategy) Descriptor() protoreflect.EnumDescriptor
func (Model_OptimizationStrategy) Enum ¶
func (x Model_OptimizationStrategy) Enum() *Model_OptimizationStrategy
func (Model_OptimizationStrategy) EnumDescriptor
deprecated
func (Model_OptimizationStrategy) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_OptimizationStrategy.Descriptor instead.
func (Model_OptimizationStrategy) Number ¶
func (x Model_OptimizationStrategy) Number() protoreflect.EnumNumber
func (Model_OptimizationStrategy) String ¶
func (x Model_OptimizationStrategy) String() string
func (Model_OptimizationStrategy) Type ¶
func (Model_OptimizationStrategy) Type() protoreflect.EnumType
type Model_RankingMetrics ¶
type Model_RankingMetrics struct { // Calculates a precision per user for all the items by ranking them and // then averages all the precisions across all the users. MeanAveragePrecision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_average_precision,json=meanAveragePrecision,proto3" json:"mean_average_precision,omitempty"` // Similar to the mean squared error computed in regression and explicit // recommendation models except instead of computing the rating directly, // the output from evaluate is computed against a preference which is 1 or 0 // depending on if the rating exists or not. MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"` // A metric to determine the goodness of a ranking calculated from the // predicted confidence by comparing it to an ideal rank measured by the // original ratings. NormalizedDiscountedCumulativeGain *wrapperspb.DoubleValue `` /* 167-byte string literal not displayed */ // Determines the goodness of a ranking by computing the percentile rank // from the predicted confidence and dividing it by the original rank. AverageRank *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=average_rank,json=averageRank,proto3" json:"average_rank,omitempty"` // contains filtered or unexported fields }
Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
func (*Model_RankingMetrics) Descriptor
deprecated
func (*Model_RankingMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_RankingMetrics.ProtoReflect.Descriptor instead.
func (*Model_RankingMetrics) GetAverageRank ¶
func (x *Model_RankingMetrics) GetAverageRank() *wrapperspb.DoubleValue
func (*Model_RankingMetrics) GetMeanAveragePrecision ¶
func (x *Model_RankingMetrics) GetMeanAveragePrecision() *wrapperspb.DoubleValue
func (*Model_RankingMetrics) GetMeanSquaredError ¶
func (x *Model_RankingMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue
func (*Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain ¶
func (x *Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain() *wrapperspb.DoubleValue
func (*Model_RankingMetrics) ProtoMessage ¶
func (*Model_RankingMetrics) ProtoMessage()
func (*Model_RankingMetrics) ProtoReflect ¶
func (x *Model_RankingMetrics) ProtoReflect() protoreflect.Message
func (*Model_RankingMetrics) Reset ¶
func (x *Model_RankingMetrics) Reset()
func (*Model_RankingMetrics) String ¶
func (x *Model_RankingMetrics) String() string
type Model_RegressionMetrics ¶
type Model_RegressionMetrics struct { // Mean absolute error. MeanAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_absolute_error,json=meanAbsoluteError,proto3" json:"mean_absolute_error,omitempty"` // Mean squared error. MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"` // Mean squared log error. MeanSquaredLogError *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=mean_squared_log_error,json=meanSquaredLogError,proto3" json:"mean_squared_log_error,omitempty"` // Median absolute error. MedianAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=median_absolute_error,json=medianAbsoluteError,proto3" json:"median_absolute_error,omitempty"` // R^2 score. RSquared *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=r_squared,json=rSquared,proto3" json:"r_squared,omitempty"` // contains filtered or unexported fields }
Evaluation metrics for regression and explicit feedback type matrix factorization models.
func (*Model_RegressionMetrics) Descriptor
deprecated
func (*Model_RegressionMetrics) Descriptor() ([]byte, []int)
Deprecated: Use Model_RegressionMetrics.ProtoReflect.Descriptor instead.
func (*Model_RegressionMetrics) GetMeanAbsoluteError ¶
func (x *Model_RegressionMetrics) GetMeanAbsoluteError() *wrapperspb.DoubleValue
func (*Model_RegressionMetrics) GetMeanSquaredError ¶
func (x *Model_RegressionMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue
func (*Model_RegressionMetrics) GetMeanSquaredLogError ¶
func (x *Model_RegressionMetrics) GetMeanSquaredLogError() *wrapperspb.DoubleValue
func (*Model_RegressionMetrics) GetMedianAbsoluteError ¶
func (x *Model_RegressionMetrics) GetMedianAbsoluteError() *wrapperspb.DoubleValue
func (*Model_RegressionMetrics) GetRSquared ¶
func (x *Model_RegressionMetrics) GetRSquared() *wrapperspb.DoubleValue
func (*Model_RegressionMetrics) ProtoMessage ¶
func (*Model_RegressionMetrics) ProtoMessage()
func (*Model_RegressionMetrics) ProtoReflect ¶
func (x *Model_RegressionMetrics) ProtoReflect() protoreflect.Message
func (*Model_RegressionMetrics) Reset ¶
func (x *Model_RegressionMetrics) Reset()
func (*Model_RegressionMetrics) String ¶
func (x *Model_RegressionMetrics) String() string
type Model_SeasonalPeriod ¶
type Model_SeasonalPeriod struct {
// contains filtered or unexported fields
}
func (*Model_SeasonalPeriod) Descriptor
deprecated
func (*Model_SeasonalPeriod) Descriptor() ([]byte, []int)
Deprecated: Use Model_SeasonalPeriod.ProtoReflect.Descriptor instead.
func (*Model_SeasonalPeriod) ProtoMessage ¶
func (*Model_SeasonalPeriod) ProtoMessage()
func (*Model_SeasonalPeriod) ProtoReflect ¶
func (x *Model_SeasonalPeriod) ProtoReflect() protoreflect.Message
func (*Model_SeasonalPeriod) Reset ¶
func (x *Model_SeasonalPeriod) Reset()
func (*Model_SeasonalPeriod) String ¶
func (x *Model_SeasonalPeriod) String() string
type Model_SeasonalPeriod_SeasonalPeriodType ¶
type Model_SeasonalPeriod_SeasonalPeriodType int32
const ( Model_SeasonalPeriod_SEASONAL_PERIOD_TYPE_UNSPECIFIED Model_SeasonalPeriod_SeasonalPeriodType = 0 // No seasonality Model_SeasonalPeriod_NO_SEASONALITY Model_SeasonalPeriod_SeasonalPeriodType = 1 // Daily period, 24 hours. Model_SeasonalPeriod_DAILY Model_SeasonalPeriod_SeasonalPeriodType = 2 // Weekly period, 7 days. Model_SeasonalPeriod_WEEKLY Model_SeasonalPeriod_SeasonalPeriodType = 3 // Monthly period, 30 days or irregular. Model_SeasonalPeriod_MONTHLY Model_SeasonalPeriod_SeasonalPeriodType = 4 // Quarterly period, 90 days or irregular. Model_SeasonalPeriod_QUARTERLY Model_SeasonalPeriod_SeasonalPeriodType = 5 // Yearly period, 365 days or irregular. Model_SeasonalPeriod_YEARLY Model_SeasonalPeriod_SeasonalPeriodType = 6 )
func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor ¶
func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor() protoreflect.EnumDescriptor
func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor
deprecated
func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor() ([]byte, []int)
Deprecated: Use Model_SeasonalPeriod_SeasonalPeriodType.Descriptor instead.
func (Model_SeasonalPeriod_SeasonalPeriodType) Number ¶
func (x Model_SeasonalPeriod_SeasonalPeriodType) Number() protoreflect.EnumNumber
func (Model_SeasonalPeriod_SeasonalPeriodType) String ¶
func (x Model_SeasonalPeriod_SeasonalPeriodType) String() string
func (Model_SeasonalPeriod_SeasonalPeriodType) Type ¶
func (Model_SeasonalPeriod_SeasonalPeriodType) Type() protoreflect.EnumType
type Model_TrainingRun ¶
type Model_TrainingRun struct { // Options that were used for this training run, includes // user specified and default options that were used. TrainingOptions *Model_TrainingRun_TrainingOptions `protobuf:"bytes,1,opt,name=training_options,json=trainingOptions,proto3" json:"training_options,omitempty"` // The start time of this training run. StartTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"` // Output of each iteration run, results.size() <= max_iterations. Results []*Model_TrainingRun_IterationResult `protobuf:"bytes,6,rep,name=results,proto3" json:"results,omitempty"` // The evaluation metrics over training/eval data that were computed at the // end of training. EvaluationMetrics *Model_EvaluationMetrics `protobuf:"bytes,7,opt,name=evaluation_metrics,json=evaluationMetrics,proto3" json:"evaluation_metrics,omitempty"` // Data split result of the training run. Only set when the input data is // actually split. DataSplitResult *Model_DataSplitResult `protobuf:"bytes,9,opt,name=data_split_result,json=dataSplitResult,proto3" json:"data_split_result,omitempty"` // Global explanations for important features of the model. For multi-class // models, there is one entry for each label class. For other models, there // is only one entry in the list. GlobalExplanations []*Model_GlobalExplanation `protobuf:"bytes,10,rep,name=global_explanations,json=globalExplanations,proto3" json:"global_explanations,omitempty"` // contains filtered or unexported fields }
Information about a single training query run for the model.
func (*Model_TrainingRun) Descriptor
deprecated
func (*Model_TrainingRun) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun) GetDataSplitResult ¶
func (x *Model_TrainingRun) GetDataSplitResult() *Model_DataSplitResult
func (*Model_TrainingRun) GetEvaluationMetrics ¶
func (x *Model_TrainingRun) GetEvaluationMetrics() *Model_EvaluationMetrics
func (*Model_TrainingRun) GetGlobalExplanations ¶
func (x *Model_TrainingRun) GetGlobalExplanations() []*Model_GlobalExplanation
func (*Model_TrainingRun) GetResults ¶
func (x *Model_TrainingRun) GetResults() []*Model_TrainingRun_IterationResult
func (*Model_TrainingRun) GetStartTime ¶
func (x *Model_TrainingRun) GetStartTime() *timestamppb.Timestamp
func (*Model_TrainingRun) GetTrainingOptions ¶
func (x *Model_TrainingRun) GetTrainingOptions() *Model_TrainingRun_TrainingOptions
func (*Model_TrainingRun) ProtoMessage ¶
func (*Model_TrainingRun) ProtoMessage()
func (*Model_TrainingRun) ProtoReflect ¶
func (x *Model_TrainingRun) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun) Reset ¶
func (x *Model_TrainingRun) Reset()
func (*Model_TrainingRun) String ¶
func (x *Model_TrainingRun) String() string
type Model_TrainingRun_IterationResult ¶
type Model_TrainingRun_IterationResult struct { // Index of the iteration, 0 based. Index *wrapperspb.Int32Value `protobuf:"bytes,1,opt,name=index,proto3" json:"index,omitempty"` // Time taken to run the iteration in milliseconds. DurationMs *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=duration_ms,json=durationMs,proto3" json:"duration_ms,omitempty"` // Loss computed on the training data at the end of iteration. TrainingLoss *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=training_loss,json=trainingLoss,proto3" json:"training_loss,omitempty"` // Loss computed on the eval data at the end of iteration. EvalLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=eval_loss,json=evalLoss,proto3" json:"eval_loss,omitempty"` // Learn rate used for this iteration. LearnRate float64 `protobuf:"fixed64,7,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"` // Information about top clusters for clustering models. ClusterInfos []*Model_TrainingRun_IterationResult_ClusterInfo `protobuf:"bytes,8,rep,name=cluster_infos,json=clusterInfos,proto3" json:"cluster_infos,omitempty"` ArimaResult *Model_TrainingRun_IterationResult_ArimaResult `protobuf:"bytes,9,opt,name=arima_result,json=arimaResult,proto3" json:"arima_result,omitempty"` // contains filtered or unexported fields }
Information about a single iteration of the training run.
func (*Model_TrainingRun_IterationResult) Descriptor
deprecated
func (*Model_TrainingRun_IterationResult) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_IterationResult.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_IterationResult) GetArimaResult ¶
func (x *Model_TrainingRun_IterationResult) GetArimaResult() *Model_TrainingRun_IterationResult_ArimaResult
func (*Model_TrainingRun_IterationResult) GetClusterInfos ¶
func (x *Model_TrainingRun_IterationResult) GetClusterInfos() []*Model_TrainingRun_IterationResult_ClusterInfo
func (*Model_TrainingRun_IterationResult) GetDurationMs ¶
func (x *Model_TrainingRun_IterationResult) GetDurationMs() *wrapperspb.Int64Value
func (*Model_TrainingRun_IterationResult) GetEvalLoss ¶
func (x *Model_TrainingRun_IterationResult) GetEvalLoss() *wrapperspb.DoubleValue
func (*Model_TrainingRun_IterationResult) GetIndex ¶
func (x *Model_TrainingRun_IterationResult) GetIndex() *wrapperspb.Int32Value
func (*Model_TrainingRun_IterationResult) GetLearnRate ¶
func (x *Model_TrainingRun_IterationResult) GetLearnRate() float64
func (*Model_TrainingRun_IterationResult) GetTrainingLoss ¶
func (x *Model_TrainingRun_IterationResult) GetTrainingLoss() *wrapperspb.DoubleValue
func (*Model_TrainingRun_IterationResult) ProtoMessage ¶
func (*Model_TrainingRun_IterationResult) ProtoMessage()
func (*Model_TrainingRun_IterationResult) ProtoReflect ¶
func (x *Model_TrainingRun_IterationResult) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_IterationResult) Reset ¶
func (x *Model_TrainingRun_IterationResult) Reset()
func (*Model_TrainingRun_IterationResult) String ¶
func (x *Model_TrainingRun_IterationResult) String() string
type Model_TrainingRun_IterationResult_ArimaResult ¶
type Model_TrainingRun_IterationResult_ArimaResult struct { // This message is repeated because there are multiple arima models // fitted in auto-arima. For non-auto-arima model, its size is one. ArimaModelInfo []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo `protobuf:"bytes,1,rep,name=arima_model_info,json=arimaModelInfo,proto3" json:"arima_model_info,omitempty"` // Seasonal periods. Repeated because multiple periods are supported for // one time series. SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `` /* 184-byte string literal not displayed */ // contains filtered or unexported fields }
(Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.
func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor
deprecated
func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo() []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo
func (*Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage ¶
func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage()
func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_IterationResult_ArimaResult) Reset ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult) Reset()
func (*Model_TrainingRun_IterationResult_ArimaResult) String ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult) String() string
type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients ¶
type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients struct { // Auto-regressive coefficients, an array of double. AutoRegressiveCoefficients []float64 `` /* 150-byte string literal not displayed */ // Moving-average coefficients, an array of double. MovingAverageCoefficients []float64 `` /* 147-byte string literal not displayed */ // Intercept coefficient, just a double not an array. InterceptCoefficient float64 `protobuf:"fixed64,3,opt,name=intercept_coefficient,json=interceptCoefficient,proto3" json:"intercept_coefficient,omitempty"` // contains filtered or unexported fields }
Arima coefficients.
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor
deprecated
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients() []float64
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient() float64
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients() []float64
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage ¶
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage()
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset()
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String() string
type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo ¶
type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo struct { // Non-seasonal order. NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"` // Arima coefficients. ArimaCoefficients *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients `protobuf:"bytes,2,opt,name=arima_coefficients,json=arimaCoefficients,proto3" json:"arima_coefficients,omitempty"` // Arima fitting metrics. ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,3,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"` // Whether Arima model fitted with drift or not. It is always false // when d is not 1. HasDrift bool `protobuf:"varint,4,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"` // The id to indicate different time series. TimeSeriesId string `protobuf:"bytes,5,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"` // Seasonal periods. Repeated because multiple periods are supported // for one time series. SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `` /* 184-byte string literal not displayed */ // contains filtered or unexported fields }
Arima model information.
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor
deprecated
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients() *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics() *Model_ArimaFittingMetrics
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift() bool
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder() *Model_ArimaOrder
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId() string
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage ¶
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage()
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset()
func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String ¶
func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String() string
type Model_TrainingRun_IterationResult_ClusterInfo ¶
type Model_TrainingRun_IterationResult_ClusterInfo struct { // Centroid id. CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"` // Cluster radius, the average distance from centroid // to each point assigned to the cluster. ClusterRadius *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=cluster_radius,json=clusterRadius,proto3" json:"cluster_radius,omitempty"` // Cluster size, the total number of points assigned to the cluster. ClusterSize *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=cluster_size,json=clusterSize,proto3" json:"cluster_size,omitempty"` // contains filtered or unexported fields }
Information about a single cluster for clustering model.
func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor
deprecated
func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_IterationResult_ClusterInfo.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId() int64
func (*Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius() *wrapperspb.DoubleValue
func (*Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize() *wrapperspb.Int64Value
func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage ¶
func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage()
func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_IterationResult_ClusterInfo) Reset ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) Reset()
func (*Model_TrainingRun_IterationResult_ClusterInfo) String ¶
func (x *Model_TrainingRun_IterationResult_ClusterInfo) String() string
type Model_TrainingRun_TrainingOptions ¶
type Model_TrainingRun_TrainingOptions struct { // The maximum number of iterations in training. Used only for iterative // training algorithms. MaxIterations int64 `protobuf:"varint,1,opt,name=max_iterations,json=maxIterations,proto3" json:"max_iterations,omitempty"` // Type of loss function used during training run. LossType Model_LossType `` /* 131-byte string literal not displayed */ // Learning rate in training. Used only for iterative training algorithms. LearnRate float64 `protobuf:"fixed64,3,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"` // L1 regularization coefficient. L1Regularization *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=l1_regularization,json=l1Regularization,proto3" json:"l1_regularization,omitempty"` // L2 regularization coefficient. L2Regularization *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=l2_regularization,json=l2Regularization,proto3" json:"l2_regularization,omitempty"` // When early_stop is true, stops training when accuracy improvement is // less than 'min_relative_progress'. Used only for iterative training // algorithms. MinRelativeProgress *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=min_relative_progress,json=minRelativeProgress,proto3" json:"min_relative_progress,omitempty"` // Whether to train a model from the last checkpoint. WarmStart *wrapperspb.BoolValue `protobuf:"bytes,7,opt,name=warm_start,json=warmStart,proto3" json:"warm_start,omitempty"` // Whether to stop early when the loss doesn't improve significantly // any more (compared to min_relative_progress). Used only for iterative // training algorithms. EarlyStop *wrapperspb.BoolValue `protobuf:"bytes,8,opt,name=early_stop,json=earlyStop,proto3" json:"early_stop,omitempty"` // Name of input label columns in training data. InputLabelColumns []string `protobuf:"bytes,9,rep,name=input_label_columns,json=inputLabelColumns,proto3" json:"input_label_columns,omitempty"` // The data split type for training and evaluation, e.g. RANDOM. DataSplitMethod Model_DataSplitMethod `` /* 162-byte string literal not displayed */ // The fraction of evaluation data over the whole input data. The rest // of data will be used as training data. The format should be double. // Accurate to two decimal places. // Default value is 0.2. DataSplitEvalFraction float64 `` /* 131-byte string literal not displayed */ // The column to split data with. This column won't be used as a // feature. // 1. When data_split_method is CUSTOM, the corresponding column should // be boolean. The rows with true value tag are eval data, and the false // are training data. // 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION // rows (from smallest to largest) in the corresponding column are used // as training data, and the rest are eval data. It respects the order // in Orderable data types: // https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties DataSplitColumn string `protobuf:"bytes,12,opt,name=data_split_column,json=dataSplitColumn,proto3" json:"data_split_column,omitempty"` // The strategy to determine learn rate for the current iteration. LearnRateStrategy Model_LearnRateStrategy `` /* 170-byte string literal not displayed */ // Specifies the initial learning rate for the line search learn rate // strategy. InitialLearnRate float64 `protobuf:"fixed64,16,opt,name=initial_learn_rate,json=initialLearnRate,proto3" json:"initial_learn_rate,omitempty"` // Weights associated with each label class, for rebalancing the // training data. Only applicable for classification models. LabelClassWeights map[string]float64 `` /* 205-byte string literal not displayed */ // User column specified for matrix factorization models. UserColumn string `protobuf:"bytes,18,opt,name=user_column,json=userColumn,proto3" json:"user_column,omitempty"` // Item column specified for matrix factorization models. ItemColumn string `protobuf:"bytes,19,opt,name=item_column,json=itemColumn,proto3" json:"item_column,omitempty"` // Distance type for clustering models. DistanceType Model_DistanceType `` /* 148-byte string literal not displayed */ // Number of clusters for clustering models. NumClusters int64 `protobuf:"varint,21,opt,name=num_clusters,json=numClusters,proto3" json:"num_clusters,omitempty"` // [Beta] Google Cloud Storage URI from which the model was imported. Only // applicable for imported models. ModelUri string `protobuf:"bytes,22,opt,name=model_uri,json=modelUri,proto3" json:"model_uri,omitempty"` // Optimization strategy for training linear regression models. OptimizationStrategy Model_OptimizationStrategy `` /* 180-byte string literal not displayed */ // Hidden units for dnn models. HiddenUnits []int64 `protobuf:"varint,24,rep,packed,name=hidden_units,json=hiddenUnits,proto3" json:"hidden_units,omitempty"` // Batch size for dnn models. BatchSize int64 `protobuf:"varint,25,opt,name=batch_size,json=batchSize,proto3" json:"batch_size,omitempty"` // Dropout probability for dnn models. Dropout *wrapperspb.DoubleValue `protobuf:"bytes,26,opt,name=dropout,proto3" json:"dropout,omitempty"` // Maximum depth of a tree for boosted tree models. MaxTreeDepth int64 `protobuf:"varint,27,opt,name=max_tree_depth,json=maxTreeDepth,proto3" json:"max_tree_depth,omitempty"` // Subsample fraction of the training data to grow tree to prevent // overfitting for boosted tree models. Subsample float64 `protobuf:"fixed64,28,opt,name=subsample,proto3" json:"subsample,omitempty"` // Minimum split loss for boosted tree models. MinSplitLoss *wrapperspb.DoubleValue `protobuf:"bytes,29,opt,name=min_split_loss,json=minSplitLoss,proto3" json:"min_split_loss,omitempty"` // Num factors specified for matrix factorization models. NumFactors int64 `protobuf:"varint,30,opt,name=num_factors,json=numFactors,proto3" json:"num_factors,omitempty"` // Feedback type that specifies which algorithm to run for matrix // factorization. FeedbackType Model_FeedbackType `` /* 148-byte string literal not displayed */ // Hyperparameter for matrix factoration when implicit feedback type is // specified. WalsAlpha *wrapperspb.DoubleValue `protobuf:"bytes,32,opt,name=wals_alpha,json=walsAlpha,proto3" json:"wals_alpha,omitempty"` // The method used to initialize the centroids for kmeans algorithm. KmeansInitializationMethod Model_KmeansEnums_KmeansInitializationMethod `` /* 218-byte string literal not displayed */ // The column used to provide the initial centroids for kmeans algorithm // when kmeans_initialization_method is CUSTOM. KmeansInitializationColumn string `` /* 142-byte string literal not displayed */ // Column to be designated as time series timestamp for ARIMA model. TimeSeriesTimestampColumn string `` /* 141-byte string literal not displayed */ // Column to be designated as time series data for ARIMA model. TimeSeriesDataColumn string `` /* 126-byte string literal not displayed */ // Whether to enable auto ARIMA or not. AutoArima bool `protobuf:"varint,37,opt,name=auto_arima,json=autoArima,proto3" json:"auto_arima,omitempty"` // A specification of the non-seasonal part of the ARIMA model: the three // components (p, d, q) are the AR order, the degree of differencing, and // the MA order. NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,38,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"` // The data frequency of a time series. DataFrequency Model_DataFrequency `` /* 152-byte string literal not displayed */ // Include drift when fitting an ARIMA model. IncludeDrift bool `protobuf:"varint,41,opt,name=include_drift,json=includeDrift,proto3" json:"include_drift,omitempty"` // The geographical region based on which the holidays are considered in // time series modeling. If a valid value is specified, then holiday // effects modeling is enabled. HolidayRegion Model_HolidayRegion `` /* 152-byte string literal not displayed */ // The id column that will be used to indicate different time series to // forecast in parallel. TimeSeriesIdColumn string `protobuf:"bytes,43,opt,name=time_series_id_column,json=timeSeriesIdColumn,proto3" json:"time_series_id_column,omitempty"` // The number of periods ahead that need to be forecasted. Horizon int64 `protobuf:"varint,44,opt,name=horizon,proto3" json:"horizon,omitempty"` // Whether to preserve the input structs in output feature names. // Suppose there is a struct A with field b. // When false (default), the output feature name is A_b. // When true, the output feature name is A.b. PreserveInputStructs bool `protobuf:"varint,45,opt,name=preserve_input_structs,json=preserveInputStructs,proto3" json:"preserve_input_structs,omitempty"` // The max value of non-seasonal p and q. AutoArimaMaxOrder int64 `protobuf:"varint,46,opt,name=auto_arima_max_order,json=autoArimaMaxOrder,proto3" json:"auto_arima_max_order,omitempty"` // contains filtered or unexported fields }
func (*Model_TrainingRun_TrainingOptions) Descriptor
deprecated
func (*Model_TrainingRun_TrainingOptions) Descriptor() ([]byte, []int)
Deprecated: Use Model_TrainingRun_TrainingOptions.ProtoReflect.Descriptor instead.
func (*Model_TrainingRun_TrainingOptions) GetAutoArima ¶
func (x *Model_TrainingRun_TrainingOptions) GetAutoArima() bool
func (*Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder ¶
func (x *Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder() int64
func (*Model_TrainingRun_TrainingOptions) GetBatchSize ¶
func (x *Model_TrainingRun_TrainingOptions) GetBatchSize() int64
func (*Model_TrainingRun_TrainingOptions) GetDataFrequency ¶
func (x *Model_TrainingRun_TrainingOptions) GetDataFrequency() Model_DataFrequency
func (*Model_TrainingRun_TrainingOptions) GetDataSplitColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetDataSplitColumn() string
func (*Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction ¶
func (x *Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction() float64
func (*Model_TrainingRun_TrainingOptions) GetDataSplitMethod ¶
func (x *Model_TrainingRun_TrainingOptions) GetDataSplitMethod() Model_DataSplitMethod
func (*Model_TrainingRun_TrainingOptions) GetDistanceType ¶
func (x *Model_TrainingRun_TrainingOptions) GetDistanceType() Model_DistanceType
func (*Model_TrainingRun_TrainingOptions) GetDropout ¶
func (x *Model_TrainingRun_TrainingOptions) GetDropout() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetEarlyStop ¶
func (x *Model_TrainingRun_TrainingOptions) GetEarlyStop() *wrapperspb.BoolValue
func (*Model_TrainingRun_TrainingOptions) GetFeedbackType ¶
func (x *Model_TrainingRun_TrainingOptions) GetFeedbackType() Model_FeedbackType
func (*Model_TrainingRun_TrainingOptions) GetHiddenUnits ¶
func (x *Model_TrainingRun_TrainingOptions) GetHiddenUnits() []int64
func (*Model_TrainingRun_TrainingOptions) GetHolidayRegion ¶
func (x *Model_TrainingRun_TrainingOptions) GetHolidayRegion() Model_HolidayRegion
func (*Model_TrainingRun_TrainingOptions) GetHorizon ¶
func (x *Model_TrainingRun_TrainingOptions) GetHorizon() int64
func (*Model_TrainingRun_TrainingOptions) GetIncludeDrift ¶
func (x *Model_TrainingRun_TrainingOptions) GetIncludeDrift() bool
func (*Model_TrainingRun_TrainingOptions) GetInitialLearnRate ¶
func (x *Model_TrainingRun_TrainingOptions) GetInitialLearnRate() float64
func (*Model_TrainingRun_TrainingOptions) GetInputLabelColumns ¶
func (x *Model_TrainingRun_TrainingOptions) GetInputLabelColumns() []string
func (*Model_TrainingRun_TrainingOptions) GetItemColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetItemColumn() string
func (*Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn() string
func (*Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod ¶
func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod() Model_KmeansEnums_KmeansInitializationMethod
func (*Model_TrainingRun_TrainingOptions) GetL1Regularization ¶
func (x *Model_TrainingRun_TrainingOptions) GetL1Regularization() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetL2Regularization ¶
func (x *Model_TrainingRun_TrainingOptions) GetL2Regularization() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetLabelClassWeights ¶
func (x *Model_TrainingRun_TrainingOptions) GetLabelClassWeights() map[string]float64
func (*Model_TrainingRun_TrainingOptions) GetLearnRate ¶
func (x *Model_TrainingRun_TrainingOptions) GetLearnRate() float64
func (*Model_TrainingRun_TrainingOptions) GetLearnRateStrategy ¶
func (x *Model_TrainingRun_TrainingOptions) GetLearnRateStrategy() Model_LearnRateStrategy
func (*Model_TrainingRun_TrainingOptions) GetLossType ¶
func (x *Model_TrainingRun_TrainingOptions) GetLossType() Model_LossType
func (*Model_TrainingRun_TrainingOptions) GetMaxIterations ¶
func (x *Model_TrainingRun_TrainingOptions) GetMaxIterations() int64
func (*Model_TrainingRun_TrainingOptions) GetMaxTreeDepth ¶
func (x *Model_TrainingRun_TrainingOptions) GetMaxTreeDepth() int64
func (*Model_TrainingRun_TrainingOptions) GetMinRelativeProgress ¶
func (x *Model_TrainingRun_TrainingOptions) GetMinRelativeProgress() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetMinSplitLoss ¶
func (x *Model_TrainingRun_TrainingOptions) GetMinSplitLoss() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetModelUri ¶
func (x *Model_TrainingRun_TrainingOptions) GetModelUri() string
func (*Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder ¶
func (x *Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder() *Model_ArimaOrder
func (*Model_TrainingRun_TrainingOptions) GetNumClusters ¶
func (x *Model_TrainingRun_TrainingOptions) GetNumClusters() int64
func (*Model_TrainingRun_TrainingOptions) GetNumFactors ¶
func (x *Model_TrainingRun_TrainingOptions) GetNumFactors() int64
func (*Model_TrainingRun_TrainingOptions) GetOptimizationStrategy ¶
func (x *Model_TrainingRun_TrainingOptions) GetOptimizationStrategy() Model_OptimizationStrategy
func (*Model_TrainingRun_TrainingOptions) GetPreserveInputStructs ¶
func (x *Model_TrainingRun_TrainingOptions) GetPreserveInputStructs() bool
func (*Model_TrainingRun_TrainingOptions) GetSubsample ¶
func (x *Model_TrainingRun_TrainingOptions) GetSubsample() float64
func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn() string
func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn() string
func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn() string
func (*Model_TrainingRun_TrainingOptions) GetUserColumn ¶
func (x *Model_TrainingRun_TrainingOptions) GetUserColumn() string
func (*Model_TrainingRun_TrainingOptions) GetWalsAlpha ¶
func (x *Model_TrainingRun_TrainingOptions) GetWalsAlpha() *wrapperspb.DoubleValue
func (*Model_TrainingRun_TrainingOptions) GetWarmStart ¶
func (x *Model_TrainingRun_TrainingOptions) GetWarmStart() *wrapperspb.BoolValue
func (*Model_TrainingRun_TrainingOptions) ProtoMessage ¶
func (*Model_TrainingRun_TrainingOptions) ProtoMessage()
func (*Model_TrainingRun_TrainingOptions) ProtoReflect ¶
func (x *Model_TrainingRun_TrainingOptions) ProtoReflect() protoreflect.Message
func (*Model_TrainingRun_TrainingOptions) Reset ¶
func (x *Model_TrainingRun_TrainingOptions) Reset()
func (*Model_TrainingRun_TrainingOptions) String ¶
func (x *Model_TrainingRun_TrainingOptions) String() string
type PatchModelRequest ¶
type PatchModelRequest struct { // Required. Project ID of the model to patch. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. Dataset ID of the model to patch. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // Required. Model ID of the model to patch. ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"` // Required. Patched model. // Follows RFC5789 patch semantics. Missing fields are not updated. // To clear a field, explicitly set to default value. Model *Model `protobuf:"bytes,4,opt,name=model,proto3" json:"model,omitempty"` // contains filtered or unexported fields }
func (*PatchModelRequest) Descriptor
deprecated
func (*PatchModelRequest) Descriptor() ([]byte, []int)
Deprecated: Use PatchModelRequest.ProtoReflect.Descriptor instead.
func (*PatchModelRequest) GetDatasetId ¶
func (x *PatchModelRequest) GetDatasetId() string
func (*PatchModelRequest) GetModel ¶
func (x *PatchModelRequest) GetModel() *Model
func (*PatchModelRequest) GetModelId ¶
func (x *PatchModelRequest) GetModelId() string
func (*PatchModelRequest) GetProjectId ¶
func (x *PatchModelRequest) GetProjectId() string
func (*PatchModelRequest) ProtoMessage ¶
func (*PatchModelRequest) ProtoMessage()
func (*PatchModelRequest) ProtoReflect ¶
func (x *PatchModelRequest) ProtoReflect() protoreflect.Message
func (*PatchModelRequest) Reset ¶
func (x *PatchModelRequest) Reset()
func (*PatchModelRequest) String ¶
func (x *PatchModelRequest) String() string
type StandardSqlDataType ¶
type StandardSqlDataType struct { // Required. The top level type of this field. // Can be any standard SQL data type (e.g., "INT64", "DATE", "ARRAY"). TypeKind StandardSqlDataType_TypeKind `` /* 145-byte string literal not displayed */ // Types that are assignable to SubType: // *StandardSqlDataType_ArrayElementType // *StandardSqlDataType_StructType SubType isStandardSqlDataType_SubType `protobuf_oneof:"sub_type"` // contains filtered or unexported fields }
The type of a variable, e.g., a function argument. Examples: INT64: {type_kind="INT64"} ARRAY<STRING>: {type_kind="ARRAY", array_element_type="STRING"} STRUCT<x STRING, y ARRAY<DATE>>:
{type_kind="STRUCT", struct_type={fields=[ {name="x", type={type_kind="STRING"}}, {name="y", type={type_kind="ARRAY", array_element_type="DATE"}} ]}}
func (*StandardSqlDataType) Descriptor
deprecated
func (*StandardSqlDataType) Descriptor() ([]byte, []int)
Deprecated: Use StandardSqlDataType.ProtoReflect.Descriptor instead.
func (*StandardSqlDataType) GetArrayElementType ¶
func (x *StandardSqlDataType) GetArrayElementType() *StandardSqlDataType
func (*StandardSqlDataType) GetStructType ¶
func (x *StandardSqlDataType) GetStructType() *StandardSqlStructType
func (*StandardSqlDataType) GetSubType ¶
func (m *StandardSqlDataType) GetSubType() isStandardSqlDataType_SubType
func (*StandardSqlDataType) GetTypeKind ¶
func (x *StandardSqlDataType) GetTypeKind() StandardSqlDataType_TypeKind
func (*StandardSqlDataType) ProtoMessage ¶
func (*StandardSqlDataType) ProtoMessage()
func (*StandardSqlDataType) ProtoReflect ¶
func (x *StandardSqlDataType) ProtoReflect() protoreflect.Message
func (*StandardSqlDataType) Reset ¶
func (x *StandardSqlDataType) Reset()
func (*StandardSqlDataType) String ¶
func (x *StandardSqlDataType) String() string
type StandardSqlDataType_ArrayElementType ¶
type StandardSqlDataType_ArrayElementType struct { // The type of the array's elements, if type_kind = "ARRAY". ArrayElementType *StandardSqlDataType `protobuf:"bytes,2,opt,name=array_element_type,json=arrayElementType,proto3,oneof"` }
type StandardSqlDataType_StructType ¶
type StandardSqlDataType_StructType struct { // The fields of this struct, in order, if type_kind = "STRUCT". StructType *StandardSqlStructType `protobuf:"bytes,3,opt,name=struct_type,json=structType,proto3,oneof"` }
type StandardSqlDataType_TypeKind ¶
type StandardSqlDataType_TypeKind int32
const ( // Invalid type. StandardSqlDataType_TYPE_KIND_UNSPECIFIED StandardSqlDataType_TypeKind = 0 // Encoded as a string in decimal format. StandardSqlDataType_INT64 StandardSqlDataType_TypeKind = 2 // Encoded as a boolean "false" or "true". StandardSqlDataType_BOOL StandardSqlDataType_TypeKind = 5 // Encoded as a number, or string "NaN", "Infinity" or "-Infinity". StandardSqlDataType_FLOAT64 StandardSqlDataType_TypeKind = 7 // Encoded as a string value. StandardSqlDataType_STRING StandardSqlDataType_TypeKind = 8 // Encoded as a base64 string per RFC 4648, section 4. StandardSqlDataType_BYTES StandardSqlDataType_TypeKind = 9 // Encoded as an RFC 3339 timestamp with mandatory "Z" time zone string: // 1985-04-12T23:20:50.52Z StandardSqlDataType_TIMESTAMP StandardSqlDataType_TypeKind = 19 // Encoded as RFC 3339 full-date format string: 1985-04-12 StandardSqlDataType_DATE StandardSqlDataType_TypeKind = 10 // Encoded as RFC 3339 partial-time format string: 23:20:50.52 StandardSqlDataType_TIME StandardSqlDataType_TypeKind = 20 // Encoded as RFC 3339 full-date "T" partial-time: 1985-04-12T23:20:50.52 StandardSqlDataType_DATETIME StandardSqlDataType_TypeKind = 21 // Encoded as WKT StandardSqlDataType_GEOGRAPHY StandardSqlDataType_TypeKind = 22 // Encoded as a decimal string. StandardSqlDataType_NUMERIC StandardSqlDataType_TypeKind = 23 // Encoded as a decimal string. StandardSqlDataType_BIGNUMERIC StandardSqlDataType_TypeKind = 24 // Encoded as a list with types matching Type.array_type. StandardSqlDataType_ARRAY StandardSqlDataType_TypeKind = 16 // Encoded as a list with fields of type Type.struct_type[i]. List is used // because a JSON object cannot have duplicate field names. StandardSqlDataType_STRUCT StandardSqlDataType_TypeKind = 17 )
func (StandardSqlDataType_TypeKind) Descriptor ¶
func (StandardSqlDataType_TypeKind) Descriptor() protoreflect.EnumDescriptor
func (StandardSqlDataType_TypeKind) Enum ¶
func (x StandardSqlDataType_TypeKind) Enum() *StandardSqlDataType_TypeKind
func (StandardSqlDataType_TypeKind) EnumDescriptor
deprecated
func (StandardSqlDataType_TypeKind) EnumDescriptor() ([]byte, []int)
Deprecated: Use StandardSqlDataType_TypeKind.Descriptor instead.
func (StandardSqlDataType_TypeKind) Number ¶
func (x StandardSqlDataType_TypeKind) Number() protoreflect.EnumNumber
func (StandardSqlDataType_TypeKind) String ¶
func (x StandardSqlDataType_TypeKind) String() string
func (StandardSqlDataType_TypeKind) Type ¶
func (StandardSqlDataType_TypeKind) Type() protoreflect.EnumType
type StandardSqlField ¶
type StandardSqlField struct { // Optional. The name of this field. Can be absent for struct fields. Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` // Optional. The type of this parameter. Absent if not explicitly // specified (e.g., CREATE FUNCTION statement can omit the return type; // in this case the output parameter does not have this "type" field). Type *StandardSqlDataType `protobuf:"bytes,2,opt,name=type,proto3" json:"type,omitempty"` // contains filtered or unexported fields }
A field or a column.
func (*StandardSqlField) Descriptor
deprecated
func (*StandardSqlField) Descriptor() ([]byte, []int)
Deprecated: Use StandardSqlField.ProtoReflect.Descriptor instead.
func (*StandardSqlField) GetName ¶
func (x *StandardSqlField) GetName() string
func (*StandardSqlField) GetType ¶
func (x *StandardSqlField) GetType() *StandardSqlDataType
func (*StandardSqlField) ProtoMessage ¶
func (*StandardSqlField) ProtoMessage()
func (*StandardSqlField) ProtoReflect ¶
func (x *StandardSqlField) ProtoReflect() protoreflect.Message
func (*StandardSqlField) Reset ¶
func (x *StandardSqlField) Reset()
func (*StandardSqlField) String ¶
func (x *StandardSqlField) String() string
type StandardSqlStructType ¶
type StandardSqlStructType struct { Fields []*StandardSqlField `protobuf:"bytes,1,rep,name=fields,proto3" json:"fields,omitempty"` // contains filtered or unexported fields }
func (*StandardSqlStructType) Descriptor
deprecated
func (*StandardSqlStructType) Descriptor() ([]byte, []int)
Deprecated: Use StandardSqlStructType.ProtoReflect.Descriptor instead.
func (*StandardSqlStructType) GetFields ¶
func (x *StandardSqlStructType) GetFields() []*StandardSqlField
func (*StandardSqlStructType) ProtoMessage ¶
func (*StandardSqlStructType) ProtoMessage()
func (*StandardSqlStructType) ProtoReflect ¶
func (x *StandardSqlStructType) ProtoReflect() protoreflect.Message
func (*StandardSqlStructType) Reset ¶
func (x *StandardSqlStructType) Reset()
func (*StandardSqlStructType) String ¶
func (x *StandardSqlStructType) String() string
type TableReference ¶
type TableReference struct { // Required. The ID of the project containing this table. ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"` // Required. The ID of the dataset containing this table. DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"` // Required. The ID of the table. The ID must contain only // letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum // length is 1,024 characters. Certain operations allow // suffixing of the table ID with a partition decorator, such as // `sample_table$20190123`. TableId string `protobuf:"bytes,3,opt,name=table_id,json=tableId,proto3" json:"table_id,omitempty"` // contains filtered or unexported fields }
func (*TableReference) Descriptor
deprecated
func (*TableReference) Descriptor() ([]byte, []int)
Deprecated: Use TableReference.ProtoReflect.Descriptor instead.
func (*TableReference) GetDatasetId ¶
func (x *TableReference) GetDatasetId() string
func (*TableReference) GetProjectId ¶
func (x *TableReference) GetProjectId() string
func (*TableReference) GetTableId ¶
func (x *TableReference) GetTableId() string
func (*TableReference) ProtoMessage ¶
func (*TableReference) ProtoMessage()
func (*TableReference) ProtoReflect ¶
func (x *TableReference) ProtoReflect() protoreflect.Message
func (*TableReference) Reset ¶
func (x *TableReference) Reset()
func (*TableReference) String ¶
func (x *TableReference) String() string
type UnimplementedModelServiceServer ¶
type UnimplementedModelServiceServer struct { }
UnimplementedModelServiceServer can be embedded to have forward compatible implementations.
func (*UnimplementedModelServiceServer) DeleteModel ¶
func (*UnimplementedModelServiceServer) DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error)
func (*UnimplementedModelServiceServer) GetModel ¶
func (*UnimplementedModelServiceServer) GetModel(context.Context, *GetModelRequest) (*Model, error)
func (*UnimplementedModelServiceServer) ListModels ¶
func (*UnimplementedModelServiceServer) ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
func (*UnimplementedModelServiceServer) PatchModel ¶
func (*UnimplementedModelServiceServer) PatchModel(context.Context, *PatchModelRequest) (*Model, error)