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Versions in this module

v1

v1.4.21

Jun 14, 2022

v1.4.20

May 18, 2022

v1.4.19

May 12, 2022

v1.4.18

Apr 19, 2022

v1.4.17

Apr 18, 2022

v1.4.16

Apr 18, 2022

v1.4.15

Apr 18, 2022

v1.4.14

Apr 8, 2022

v1.4.13

Mar 30, 2022

v1.4.12

Mar 23, 2022

v1.4.11

Jan 13, 2022

v1.4.10

Jan 7, 2022

v1.4.9

Jan 4, 2022

v1.4.8

Jan 4, 2022

v1.4.7

Dec 23, 2021

v1.4.6

Dec 22, 2021

v1.4.5

Dec 8, 2021

v1.4.4

Nov 15, 2021

v1.4.3

Nov 12, 2021

v1.4.2

Sep 26, 2021

v1.4.1

Sep 26, 2021

v1.4.0

Sep 26, 2021

v1.3.7

Nov 16, 2021

v1.3.6

Sep 19, 2021

v1.3.5

Sep 18, 2021

Changes in this version

+ func AbsoluteError(a, b []float64) []float64

+ func Accuracy(data []metrics) float64

+ func Bhattacharyya(p, q []float64) float64

+ func BoundingBoxIntersectionOverUnion(boxA, boxB *dlframework.BoundingBox) float64

+ func BoundingBoxJaccard(boxA, boxB *dlframework.BoundingBox) float64

+ func Broadcast(a float64, len int) []float64

+ func CDF(data, edges []float64) (values []float64)

+ func ClassificationTop1(features *dlframework.Features, expectedLabelIndex int) bool

+ func ClassificationTop5(features *dlframework.Features, expectedLabelIndex int) bool

+ func Correlation(x, y, weights []float64) float64

+ func Covariance(x, y, weights []float64) float64

+ func Edges(data ...[]float64) []float64

+ func Expectation(data []float64) float64

+ func F1Score(data []metrics) float64

+ func Fpr(data []metrics) float64

+ func Hellinger(p, q []float64) float64

+ func Histogram(data []float64, edges []float64) (bins []uint, total uint)

+ func IntersectionOverUnion(featA, featB *dlframework.Feature) float64

+ func Jaccard(featA, featB *dlframework.Feature) float64

+ func JensenShannon(p, q []float64) float64

+ func KolmogorovSmirnov(data1, data2 []float64) float64

+ func KullbackLeibler(p, q []float64) float64

+ func L2(x, y []float64) float64

+ func Mean(x []float64) float64

+ func MeanSquaredError(a, b []float64) float64

+ func MeanSquaredPercentageError(y, yhat []float64) float64

+ func NormalizedRootMeanSquaredError(y, yhat []float64) float64

+ func PDF(data, edges []float64) (values []float64)

+ func PeakSignalToNoiseRatio(input, reference []float64) float64

+ func Precision(data []metrics) float64

+ func Recall(data []metrics) float64

+ func RegisterFeatureCompareFunction(name string, f FeatureCompareFunction)

+ func RelativeAbsoluteError(a, b []float64) float64

+ func RootMeanSquaredError(y, yhat []float64) float64

+ func RootMeanSquaredPercentageError(y, yhat []float64) float64

+ func SquaredError(a, b []float64) []float64

+ func SquaredLogError(a, b []float64) []float64

+ func Sum(s []float64) float64

+ func Top1(features *dlframework.Features, expectedLabelIndex int) bool

+ func Top5(features *dlframework.Features, expectedLabelIndex int) bool

+ func Uniform(x, y []float64) float64

+ func Variance(data []float64) float64

+ func WeightedMean(x, weights []float64) float64

+ type FeatureCompareFunction func(actual *dlframework.Features, expected interface{}) float64

+ func GetFeatureCompareFunction(name string) FeatureCompareFunction