Metrics: Evaluation Metrics for Machine Learning

An implementation of evaluation metrics in R that are commonly used in supervised machine learning. It implements metrics for regression, time series, binary classification, classification, and information retrieval problems. It has zero dependencies and a consistent, simple interface for all functions.

Version: 0.1.4
Suggests: testthat
Published: 2018-07-09
Author: Ben Hamner [aut, cph], Michael Frasco [aut, cre], Erin LeDell [ctb]
Maintainer: Michael Frasco <mfrasco6 at gmail.com>
BugReports: https://github.com/mfrasco/Metrics/issues
License: BSD_3_clause + file LICENSE
URL: https://github.com/mfrasco/Metrics
NeedsCompilation: no
CRAN checks: Metrics results

Downloads:

Reference manual: Metrics.pdf
Package source: Metrics_0.1.4.tar.gz
Windows binaries: r-devel: Metrics_0.1.4.zip, r-release: Metrics_0.1.4.zip, r-oldrel: Metrics_0.1.4.zip
OS X binaries: r-release: Metrics_0.1.4.tgz, r-oldrel: Metrics_0.1.4.tgz
Old sources: Metrics archive

Reverse dependencies:

Reverse imports: dblr, iml, predtoolsTS, specmine
Reverse suggests: featurefinder

Linking:

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