Evaluation metrics for machine learning

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Documentation for package ‘Metrics’ version 0.1.1

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ae Compute the absolute error#' This function computes the elementwise absolute error for a number or a vector
apk Compute the average precision at k
auc Compute the area under the ROC (AUC)
ce Compute the classification error
ll Compute the log loss
logLoss Compute the mean log loss
mae Compute the mean absolute error#' This function computes the mean absolte error between two vectors
mapk Compute the mean average precision at k
MeanQuadraticWeightedKappa Compute the mean quadratic weighted kappa
mse Compute the mean squared error#' This function computes the mean squared error between two vectors
msle Compute the mean squared log error
rmse Compute the root mean squared error#' This function computes the root mean squared error between two vectors
rmsle Compute the root mean squared log error
ScoreQuadraticWeightedKappa Compute the quadratic weighted kappa
se Compute the squared error
sle Compute the squared log error