Man pages for yanyachen/MLmetrics
Machine Learning Evaluation Metrics

AccuracyAccuracy
Area_Under_CurveCalculate the Area Under the Curve
AUCArea Under the Receiver Operating Characteristic Curve (ROC...
ConfusionDFConfusion Matrix (Data Frame Format)
ConfusionMatrixConfusion Matrix
F1_ScoreF1 Score
FBeta_ScoreF-Beta Score
GainAUCArea Under the Gain Chart
GiniGini Coefficient
KS_StatKolmogorov-Smirnov Statistic
LiftAUCArea Under the Lift Chart
LogLossLog loss / Cross-Entropy Loss
MAEMean Absolute Error Loss
MAPEMean Absolute Percentage Error Loss
MedianAEMedian Absolute Error Loss
MedianAPEMedian Absolute Percentage Error Loss
MLmetricsMLmetrics: Machine Learning Evaluation Metrics
MSEMean Square Error Loss
MultiLogLossMulti Class Log Loss
NormalizedGiniNormalized Gini Coefficient
Poisson_LogLossPoisson Log loss
PRAUCArea Under the Precision-Recall Curve (PR AUC)
PrecisionPrecision
R2_scoreR-Squared (Coefficient of Determination) Regression Score
RAERelative Absolute Error Loss
RecallRecall
RMSERoot Mean Square Error Loss
RMSLERoot Mean Squared Logarithmic Error Loss
RMSPERoot Mean Square Percentage Error Loss
RRSERoot Relative Squared Error Loss
SensitivitySensitivity
SpecificitySpecificity
ZeroOneLossNormalized Zero-One Loss (Classification Error Loss)
yanyachen/MLmetrics documentation built on May 28, 2017, 8:36 a.m.