Package: Metrics 0.1.4

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.

Authors:Ben Hamner [aut, cph], Michael Frasco [aut, cre], Erin LeDell [ctb]

Metrics_0.1.4.tar.gz
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Metrics_0.1.4.tgz(r-4.6-any)Metrics_0.1.4.tgz(r-4.5-any)
Metrics_0.1.4.tar.gz(r-4.7-any)Metrics_0.1.4.tar.gz(r-4.6-any)
Metrics_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
Metrics/json (API)

# Install 'Metrics' in R:

install.packages('Metrics', repos = c('https://mfrasco.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mfrasco/metrics/issues

On CRAN:

13.16 score 102 stars 43 packages 8.2k scripts 27k downloads 56 mentions 33 exports 0 dependencies

Last updated from:ca12765d3e. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	107
source / vignettes	OK	173
linux-release-x86_64	OK	101
macos-release-arm64	OK	140
macos-oldrel-arm64	OK	175
windows-devel	OK	77
windows-release	OK	86
windows-oldrel	OK	64
wasm-release	OK	89

Exports:accuracy ae ape apk auc bias ce explained_variation f1 fbeta_score ll logLoss mae mape mapk mase mdae MeanQuadraticWeightedKappa mse msle percent_bias precision rae recall rmse rmsle rrse rse ScoreQuadraticWeightedKappa se sle smape sse

Dependencies:

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Accuracy	accuracy
Absolute Error	ae
Absolute Percent Error	ape
Average Precision at k	apk
Area under the ROC curve (AUC)	auc
Bias	bias
Classification Error	ce
Explained Variation	explained_variation
F1 Score	f1
F-beta Score	fbeta_score
Log Loss	ll
Mean Log Loss	logLoss
Mean Absolute Error	mae
Mean Absolute Percent Error	mape
Mean Average Precision at k	mapk
Mean Absolute Scaled Error	mase
Median Absolute Error	mdae
Mean Quadratic Weighted Kappa	MeanQuadraticWeightedKappa
Mean Squared Error	mse
Mean Squared Log Error	msle
Inherit Documentation for Binary Classification Metrics	params_binary
Inherit Documentation for Classification Metrics	params_classification
Inherit Documentation for Regression Metrics	params_regression
Percent Bias	percent_bias
Precision	precision
Relative Absolute Error	rae
Recall	recall
Root Mean Squared Error	rmse
Root Mean Squared Log Error	rmsle
Root Relative Squared Error	rrse
Relative Squared Error	rse
Quadratic Weighted Kappa	ScoreQuadraticWeightedKappa
Squared Error	se
Squared Log Error	sle
Symmetric Mean Absolute Percentage Error	smape
Sum of Squared Errors	sse