cvLoss {gbev}R Documentation

Cross-validation of boosting iteration.

Description

Performs k-fold cross-validation of number of boosting iterations.

Usage

cvLoss(object,k,random=F,loss="logLike")

Arguments

object A fitted model of type gbev.object.
k Is the k in k-fold cross-validation.
random If TRUE then cross-validation is done by randomly sampling (without replacement) the validation group, else the validation groups are determined from order appearing in data.
loss Can be logLike for binary regression (negative log-likelihood loss), or L2 for squared error loss.

Value

Returns a list containing, iters which are iterations the cross-validation loss is evaluated, cvLoss which is the cross-validated loss-function, estIter which is the iteration minimizing the cross-validated loss.


[Package gbev version 0.1.1 Index]