cross_validation_split: K-fold cross validation

In stschn/deepANN: Neural Network Toolbox

K-fold cross validation

Description

cross_validation splits a data set in partial sets, so-called folds, and creates a list of folds.

Usage

cross_validation_split(dataset, folds = 3L, shuffle = FALSE)

Arguments

dataset	A data set, usually a data frame.
folds	Number of created folds.
shuffle	Controls whether the samples of the data set should be randomly shuffled before fold creation. For time series data, this argument must be set equal to FALSE because the order of the samples can't be changed.

Value

A named list with folds.

See Also

Other Machine Learning: decision_tree(), k_nearest_neighbors(), moving_average(), naive_bayes(), naive_forecast(), predict.decisiontree(), predict.kmeans(), predict.naivebayes()

stschn/deepANN documentation built on June 25, 2024, 7:27 a.m.