Man pages for mfrasco/Metrics
Evaluation Metrics for Machine Learning

aeAbsolute Error
apeAbsolute Percent Error
apkAverage Precision at k
aucArea under the ROC curve (AUC)
ceClassification Error
explained_variationExplained Variation
f1F1 Score
fbeta_scoreF-beta Score
llLog Loss
logLossMean Log Loss
maeMean Absolute Error
mapeMean Absolute Percent Error
mapkMean Average Precision at k
maseMean Absolute Scaled Error
mdaeMedian Absolute Error
MeanQuadraticWeightedKappaMean Quadratic Weighted Kappa
mseMean Squared Error
msleMean Squared Log Error
params_binaryInherit Documentation for Binary Classification Metrics
params_classificationInherit Documentation for Classification Metrics
params_regressionInherit Documentation for Regression Metrics
percent_biasPercent Bias
raeRelative Absolute Error
rmseRoot Mean Squared Error
rmsleRoot Mean Squared Log Error
rrseRoot Relative Squared Error
rseRelative Squared Error
ScoreQuadraticWeightedKappaQuadratic Weighted Kappa
seSquared Error
sleSquared Log Error
smapeSymmetric Mean Absolute Percentage Error
sseSum of Squared Errors
mfrasco/Metrics documentation built on May 13, 2019, 12:31 a.m.