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
DOI:	10.32614/CRAN.package.Metrics
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.html , 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, NumericEnsembles
Reverse imports:	adsoRptionCMF, ai, ARGOS, BayesianHybridDesign, CGMissingDataR, ConsReg, coursekata, epicasting, ExpressionCellNet, gbm.auto, heimdall, hybridts, ImFoR, iml, janus, kssa, lilikoi, manymodelr, mlr3shiny, nda, pam, poolHelper, populR, predtoolsTS, previsionio, PUPAK, PUPMSI, PWEV, RSCAT, RSP, SAMprior, scoringutils, sense, sjSDM, UEI, valueprhr, WaveletANN, WaveletETS, WaveletGBM, WaveletKNN
Reverse suggests:	cv, httkexamples, luz, PatientLevelPrediction, s2net, tfdatasets

Linking:

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