accuracy {fda.usc}R Documentation

Performance measures for regression and classification models

Description

cat2meas and tab2meas calculate the measures for a multiclass classification model.
pred2meas calculates the measures for a regression model.

Usage

cat2meas(yobs, ypred, measure = "accuracy", cost = rep(1, nlevels(yobs)))

tab2meas(tab, measure = "accuracy", cost = rep(1, nrow(tab)))

pred.MSE(yobs, ypred)

pred.RMSE(yobs, ypred)

pred.MAE(yobs, ypred)

pred2meas(yobs, ypred, measure = "RMSE")

Arguments

yobs

A vector of the labels, true class or observed response. Can be numeric, character, or factor.

ypred

A vector of the predicted labels, predicted class or predicted response. Can be numeric, character, or factor.

measure

Type of measure, see details section.

cost

Cost value by class (only for input factors).

tab

Confusion matrix (Contingency table: observed class by rows, predicted class by columns).

Details

See Also

Other performance: weights4class()


[Package fda.usc version 2.1.0 Index]