Metrics v0.1.2


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Evaluation Metrics for Machine Learning

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

Functions in Metrics

Name Description
ll Compute the log loss
mae Compute the mean absolute error#'
mapk Compute the mean average precision at k
logLoss Compute the mean log loss
auc Compute the area under the ROC (AUC)
ce Compute the classification error
se Compute the squared error
sle Compute the squared log error
mse Compute the mean squared error#'
msle Compute the mean squared log error
MeanQuadraticWeightedKappa Compute the mean quadratic weighted kappa
ScoreQuadraticWeightedKappa Compute the quadratic weighted kappa
ae Compute the absolute error#'
apk Compute the average precision at k
rmse Compute the root mean squared error#'
rmsle Compute the root mean squared log error
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License BSD
Collate 'metrics.r'
Packaged 2017-04-21 14:50:30 UTC; ripley
Repository CRAN
Date/Publication 2017-04-21 14:55:21 UTC
NeedsCompilation no
X-CRAN-Original-Maintainer Ben Hamner
X-CRAN-Comment Orphaned and corrected on 2017-04-21 as check errors were not corrected despite reminders.
suggests RUnit
Contributors Ben Hamner

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