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eve (version 1.0)

The Eigenvalues Entropy as a Classifier Evaluation Measure

Description

The confusion matrix (CM) is used to get a classifier's evaluation measure in order to select a method among many. A stochastic matrix and its transformation are computed from the CM. The eigenvalues of the transformed symmetric matrix are used to get an entropy which appears to be a good evaluation measure. Many other measures, commonly used, are provided for comparison purpose.

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Version

Install

install.packages('eve')

Monthly Downloads

179

Version

1.0

License

GPL (>= 2)

Maintainer

Doulaye Dembele

Last Published

November 11th, 2025

Functions in eve (1.0)

eve.mcen

Modified confusion entropy calculation
eve.bival

Some binary measures calculation
eve.mcc

Matthews' correlation coefficient calculation
eve.acc

Accuracy calculation
eve.nmi

Normalized mutual information calculation
eve.cen

Confusion entropy calculation
eve.bounds

Eigenvalues bounds calculation
eve.mmatt

Modified confusion matrix calculation
eve

Eigenvalue entropy calculation
eve-package

The Eigenvalues Entropy as a Classifier Evaluation Measure
eve.kappa

Cohen's Kappa calculation
eve.eigens

Eigenvalues used in the EVE measure
m2two

Conversion of a multicass confusion matrixto a single binary confusion matrix
m2two.k

Comparison of the class k versus the rest