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Metrics  

Evaluation Metrics for Machine Learning
View on CRAN: Click here


Download and install Metrics package within the R console
Install from CRAN:
install.packages("Metrics")

Install from Github:
library("remotes")
install_github("cran/Metrics")

Install by package version:
library("remotes")
install_version("Metrics", "0.1.4")



Attach the package and use:
library("Metrics")
Maintained by
Michael Frasco
[Scholar Profile | Author Map]
First Published: 2012-06-20
Latest Update: 2018-07-09
Description:
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.
How to cite:
Michael Frasco (2012). Metrics: Evaluation Metrics for Machine Learning. R package version 0.1.4, https://cran.r-project.org/web/packages/Metrics. Accessed 02 May. 2025.
Previous versions and publish date:
0.1.1 (2012-06-20 08:57), 0.1.2 (2017-04-21 16:55), 0.1.3 (2017-11-03 08:12)
Other packages that cited Metrics R package
View Metrics citation profile
Other R packages that Metrics depends, imports, suggests or enhances
Complete documentation for Metrics
Functions, R codes and Examples using the Metrics R package
Some associated functions: MeanQuadraticWeightedKappa . ScoreQuadraticWeightedKappa . accuracy . ae . ape . apk . auc . bias . ce . f1 . fbeta_score . ll . logLoss . mae . mape . mapk . mase . mdae . mse . msle . params_binary . params_classification . params_regression . percent_bias . precision . rae . recall . rmse . rmsle . rrse . rse . se . sle . smape . sse . 
Some associated R codes: binary_classification.R . classification.R . information_retrieval.R . regression.R . time_series.R .  Full Metrics package functions and examples
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