Documentation ¶
Index ¶
- Variables
- func LocateBuiltInDataset(name string, format DatasetFormat) (string, string, error)
- type BaseModel
- type DatasetFormat
- type Model
- type ParamName
- type Params
- func (parameters Params) Copy() Params
- func (parameters Params) GetBool(name ParamName, _default bool) bool
- func (parameters Params) GetFloat32(name ParamName, _default float32) float32
- func (parameters Params) GetInt(name ParamName, _default int) int
- func (parameters Params) GetInt64(name ParamName, _default int64) int64
- func (parameters Params) GetString(name ParamName, _default string) string
- func (parameters Params) Overwrite(params Params) Params
- func (parameters Params) ToString() string
- type ParamsGrid
- type Runner
- type Tracker
Constants ¶
This section is empty.
Variables ¶
The Data directories
Functions ¶
Types ¶
type BaseModel ¶
type BaseModel struct { Params Params // Hyper-parameters // contains filtered or unexported fields }
BaseModel model must be included by every recommendation model. Hyper-parameters, ID sets, random generator and fitting options are managed the BaseModel model.
func (*BaseModel) GetParams ¶
GetParams returns all hyper-parameters.
func (*BaseModel) GetRandomGenerator ¶
func (model *BaseModel) GetRandomGenerator() base.RandomGenerator
type Model ¶
type Model interface { SetParams(params Params) GetParams() Params GetParamsGrid() ParamsGrid Clear() Invalid() bool }
Model is the interface for all models. Any model in this package should implement it.
type ParamName ¶
type ParamName string
ParamName is the type of hyper-parameter names.
const ( Lr ParamName = "Lr" // learning rate Reg ParamName = "Reg" // regularization strength NEpochs ParamName = "NEpochs" // number of epochs NFactors ParamName = "NFactors" // number of factors RandomState ParamName = "RandomState" // random state (seed) InitMean ParamName = "InitMean" // mean of gaussian initial parameter InitStdDev ParamName = "InitStdDev" // standard deviation of gaussian initial parameter Alpha ParamName = "Alpha" // weight for negative samples in ALS Similarity ParamName = "Similarity" UseFeature ParamName = "UseFeature" )
Predefined hyper-parameter names
type Params ¶
type Params map[ParamName]interface{}
Params stores hyper-parameters for an model. It is a map between strings (names) and interface{}s (values). For example, hyper-parameters for SVD is given by:
base.Params{ base.Lr: 0.007, base.NEpochs: 100, base.NFactors: 80, base.Reg: 0.1, }
func (Params) GetBool ¶
GetBool gets a boolean parameter by name. Returns _default if not exists or type doesn't match.
func (Params) GetFloat32 ¶
func (Params) GetInt ¶
GetInt gets a integer parameter by name. Returns _default if not exists or type doesn't match.
func (Params) GetInt64 ¶
GetInt64 gets a int64 parameter by name. Returns _default if not exists or type doesn't match. The type will be converted if given int.
func (Params) GetString ¶
GetString gets a string parameter
type ParamsGrid ¶
type ParamsGrid map[ParamName][]interface{}
ParamsGrid contains candidate for grid search.
func (ParamsGrid) Fill ¶
func (grid ParamsGrid) Fill(_default ParamsGrid)
func (ParamsGrid) Len ¶
func (grid ParamsGrid) Len() int
func (ParamsGrid) NumCombinations ¶
func (grid ParamsGrid) NumCombinations() int
type Runner ¶
type Runner interface { Lock() UnLock() }