evaluation.kappa: Kappa evaluation of classification predictions

In fdm2id: Data Mining and R Programming for Beginners

Kappa evaluation of classification predictions

Description

Evaluation predictions of a classification model according to Cohen's kappa: the proportion of correct predictions, corrected for the proportion two independent labellings would get right by chance. Class labels being nominal, the kappa is the unweighted one – every mistake counts the same.

Usage

evaluation.kappa(predictions, gt, ...)

Arguments

predictions	The predictions of a classification model (factor or vector).
gt	The ground truth (factor or vector).
...	Other parameters.

Value

The evaluation of the predictions (numeric value).

See Also

evaluation.accuracy, evaluation.fmeasure, evaluation.fowlkesmallows, evaluation.goodness, evaluation.jaccard, evaluation.kappa, evaluation.precision, evaluation.precision, evaluation.recall, evaluation

Examples

require (datasets)
data (iris)
d = splitdata (iris, 5)
model.nb = NB (d$train.x, d$train.y)
pred.nb = predict (model.nb, d$test.x)
evaluation.kappa (pred.nb, d$test.y)

fdm2id documentation built on Aug. 28, 2026, 9:07 a.m.