SuperLearner.CV.control

Integer. Number of splits for the V-fold cross-validation step. The default is 10. In most cases, between 10 and 20 splits works well.

Logical. Should the data splits be stratified by a binary response? Attempts to maintain the same ratio in each training and validation sample.

stratifyCV

Logical. Should the rows of <code>X</code> be shuffled before creating the splits.

shuffle

A List. Use this to pass pre-specified rows for the sample splits. The length of the list should be <code>V</code> and each entry in the list should contain a vector with the row numbers of the corresponding validation sample.

validRows

Control parameters for the cross validation steps in <code>SuperLearner</code>

utilities

This package implements the super learner prediction
        method and contains a library of prediction algorithms to be
        used in the super learner.

SuperLearner.CV.control: Control parameters for the cross validation steps in `SuperLearner`

Description

Usage

Arguments

Value