evaluation

Documentation

Index

• type Evaluation
  • func NewEvaluation(usage neural.NetworkType, classes []string) *Evaluation
  • func (e *Evaluation) Add(labeledClass, predictedClass string)
  • func (e *Evaluation) AddDistance(n *neural.Network, in, ideal []float64) float64
  • func (e *Evaluation) AddRegression(label, predicted float64)
  • func (e *Evaluation) GetAccuracy(label string) float64
  • func (e *Evaluation) GetBalancedAccuracy(label string) float64
  • func (e *Evaluation) GetCorrectRatio() float64
  • func (e *Evaluation) GetDistance() float64
  • func (e *Evaluation) GetFMeasure(label string) float64
  • func (e *Evaluation) GetFallout(label string) float64
  • func (e *Evaluation) GetFalseDiscoveryRate(label string) float64
  • func (e *Evaluation) GetFalseNegatives(label string) int
  • func (e *Evaluation) GetFalsePositiveRate(label string) float64
  • func (e *Evaluation) GetFalsePositives(label string) int
  • func (e *Evaluation) GetInformedness(label string) float64
  • func (e *Evaluation) GetMarkedness(label string) float64
  • func (e *Evaluation) GetNegativePredictionValue(label string) float64
  • func (e *Evaluation) GetNegatives(label string) int
  • func (e *Evaluation) GetOverallAccuracy() float64
  • func (e *Evaluation) GetOverallBalancedAccuracy() float64
  • func (e *Evaluation) GetOverallFMeasure() float64
  • func (e *Evaluation) GetPositives(label string) int
  • func (e *Evaluation) GetPrecision(label string) float64
  • func (e *Evaluation) GetRecall(label string) float64
  • func (e *Evaluation) GetSensitivity(label string) float64
  • func (e *Evaluation) GetSpecificity(label string) float64
  • func (e *Evaluation) GetTrueNegatives(label string) int
  • func (e *Evaluation) GetTruePositives(label string) int
  • func (e *Evaluation) PrintConfusionMatrix()
  • func (e *Evaluation) PrintRegressionSummary()
  • func (e *Evaluation) PrintSummaries()
  • func (e *Evaluation) PrintSummary(label string)
  • func (e *Evaluation) SetRegressionThreshold(threshold float64)

Types

type Evaluation

type Evaluation struct {
	Confusion       map[string]map[string]int
	Correct         int
	Wrong           int
	OverallDistance float64
	Usage           neural.NetworkType
	Threshold       float64
}

Evaluation contains all the structures necessary for the evaluation

func NewEvaluation

func NewEvaluation(usage neural.NetworkType, classes []string) *Evaluation

NewEvaluation creates a new evaluation object

func (*Evaluation) Add

func (e *Evaluation) Add(labeledClass, predictedClass string)

Add adds a new data point to the evaluation

func (*Evaluation) AddDistance

func (e *Evaluation) AddDistance(n *neural.Network, in, ideal []float64) float64

AddDistance adds distance between ideal output and output of the network

func (*Evaluation) AddRegression

func (e *Evaluation) AddRegression(label, predicted float64)

AddRegression add a predicted regresssion value to tht set

func (*Evaluation) GetAccuracy

func (e *Evaluation) GetAccuracy(label string) float64

GetAccuracy (TP+TN) / (P+N)

func (*Evaluation) GetBalancedAccuracy

func (e *Evaluation) GetBalancedAccuracy(label string) float64

GetBalancedAccuracy (TP/P + TN/N) / 2

func (*Evaluation) GetCorrectRatio

func (e *Evaluation) GetCorrectRatio() float64

GetCorrectRatio returns correct classified samples ratio

func (*Evaluation) GetDistance

func (e *Evaluation) GetDistance() float64

GetDistance returns the distance from the evaluation

func (*Evaluation) GetFMeasure

func (e *Evaluation) GetFMeasure(label string) float64

GetFMeasure 2TP/(2TP+FP+FN)

func (*Evaluation) GetFallout

func (e *Evaluation) GetFallout(label string) float64

GetFallout FP / N

func (*Evaluation) GetFalseDiscoveryRate

func (e *Evaluation) GetFalseDiscoveryRate(label string) float64

GetFalseDiscoveryRate FP / (FP+TP)

func (*Evaluation) GetFalseNegatives

func (e *Evaluation) GetFalseNegatives(label string) int

GetFalseNegatives returns FNs

func (*Evaluation) GetFalsePositiveRate

func (e *Evaluation) GetFalsePositiveRate(label string) float64

GetFalsePositiveRate same as fallout

func (*Evaluation) GetFalsePositives

func (e *Evaluation) GetFalsePositives(label string) int

GetFalsePositives returns FP

func (*Evaluation) GetInformedness

func (e *Evaluation) GetInformedness(label string) float64

GetInformedness = Sensitivity + Specificity − 1

func (*Evaluation) GetMarkedness

func (e *Evaluation) GetMarkedness(label string) float64

GetMarkedness = Precision + NegativePredictionValue − 1

func (*Evaluation) GetNegativePredictionValue

func (e *Evaluation) GetNegativePredictionValue(label string) float64

GetNegativePredictionValue TN/(TN+FN)

func (*Evaluation) GetNegatives

func (e *Evaluation) GetNegatives(label string) int

GetNegatives FP + TN

func (*Evaluation) GetOverallAccuracy

func (e *Evaluation) GetOverallAccuracy() float64

GetOverallAccuracy calculates for the training evaluation

func (*Evaluation) GetOverallBalancedAccuracy

func (e *Evaluation) GetOverallBalancedAccuracy() float64

GetOverallBalancedAccuracy calculates for the training evaluation

func (*Evaluation) GetOverallFMeasure

func (e *Evaluation) GetOverallFMeasure() float64

GetOverallFMeasure calculates for the training evaluation

func (*Evaluation) GetPositives

func (e *Evaluation) GetPositives(label string) int

GetPositives TP + FN

func (*Evaluation) GetPrecision

func (e *Evaluation) GetPrecision(label string) float64

GetPrecision TP/(TP+FP)

func (*Evaluation) GetRecall

func (e *Evaluation) GetRecall(label string) float64

GetRecall TP/P, TP/(TP + FN)

func (*Evaluation) GetSensitivity

func (e *Evaluation) GetSensitivity(label string) float64

GetSensitivity like recall

func (*Evaluation) GetSpecificity

func (e *Evaluation) GetSpecificity(label string) float64

GetSpecificity TN / N, TN/(FP+TN)

func (*Evaluation) GetTrueNegatives

func (e *Evaluation) GetTrueNegatives(label string) int

GetTrueNegatives returns TN

func (*Evaluation) GetTruePositives

func (e *Evaluation) GetTruePositives(label string) int

GetTruePositives returns TP

func (*Evaluation) PrintConfusionMatrix

func (e *Evaluation) PrintConfusionMatrix()

PrintConfusionMatrix prints the confusion matrix of the evaluation

func (*Evaluation) PrintRegressionSummary

func (e *Evaluation) PrintRegressionSummary()

PrintRegressionSummary returns a summary of the evaluated regression

func (*Evaluation) PrintSummaries

func (e *Evaluation) PrintSummaries()

PrintSummaries prints the summaries of all classes

func (*Evaluation) PrintSummary

func (e *Evaluation) PrintSummary(label string)

PrintSummary returns a summary

func (*Evaluation) SetRegressionThreshold

func (e *Evaluation) SetRegressionThreshold(threshold float64)

SetRegressionThreshold sets the threshold if you are trying to do Pos / Neg with a regressor