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Metrics (version 0.1.1)

Evaluation metrics for machine learning

Description

Metrics is a set of evaluation metrics that is commonly used in supervised machine learning.

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Install

install.packages('Metrics')

Monthly Downloads

31,586

Version

0.1.1

License

BSD

Issues

12

Pull Requests

24

Stars

1,636

Forks

455

Maintainer

Ben Hamner

Last Published

June 20th, 2012

Functions in Metrics (0.1.1)

mapk

Compute the mean average precision at k
ll

Compute the log loss
MeanQuadraticWeightedKappa

Compute the mean quadratic weighted kappa
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
mse

Compute the mean squared error#' This function computes the mean squared error between two vectors
logLoss

Compute the mean log loss
mae

Compute the mean absolute error#' This function computes the mean absolte error between two vectors
auc

Compute the area under the ROC (AUC)
ce

Compute the classification error
rmse

Compute the root mean squared error#' This function computes the root mean squared error between two vectors
msle

Compute the mean squared log error
ScoreQuadraticWeightedKappa

Compute the quadratic weighted kappa
sle

Compute the squared log error
se

Compute the squared error
rmsle

Compute the root mean squared log error