caretEnsemble (version 1.0.0)

greedOptAUC: Greedy optimization of the area under the curve

Description

This algorithm optimizes the area under the curve for classification models

Usage

greedOptAUC(X, Y, iter = 100L)

Arguments

X

the matrix of predictors

Y

the dependent variable

iter

an integer for the number of iterations

Value

• A numeric of the weights for each model.

Details

If the optimization fails to produce an error term better than the best component model, a message is returned and the best optimization after N iterations is returned.

Examples

x <- matrix(runif(10), ncol=2)
y <- sample(c('Y', 'N'), 5, replace=TRUE)
greedOptAUC(x, y, iter = 2L)