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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

Documentation:

Reference manual: Metrics.pdf

Downloads:

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
macOS binaries: r-release (arm64): Metrics_0.1.4.tgz, r-oldrel (arm64): Metrics_0.1.4.tgz, r-release (x86_64): Metrics_0.1.4.tgz, r-oldrel (x86_64): Metrics_0.1.4.tgz
Old sources: Metrics archive

Reverse dependencies:

Reverse depends: Greymodels, manymodelr, SAMprior
Reverse imports: ARGOS, audrex, ConsReg, dblr, epicasting, gbm.auto, hybridts, ImFoR, iml, immuneSIM, janus, kssa, lilikoi, MetaIntegrator, mlr3shiny, OptiSembleForecasting, phytoclass, poolHelper, populR, predtoolsTS, previsionio, PUPAIM, PUPAK, PUPMSI, PWEV, RSCAT, RSP, sense, sjSDM, superml, WaveletANN, WaveletETS, WaveletGBM, WaveletKNN
Reverse suggests: cv, featurefinder, luz, s2net, tfdatasets

Linking:

Please use the canonical form https://CRAN.R-project.org/package=Metrics to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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