Represents an algorithm that realizes a split of a given multilabel instances in folds, given a seed, custom information about the split represented as a string, and the fold that is left out for testing.
Generates a purely random split of the dataset depending on the seed and on the portions provided.
Makes use of the WekaUtil to split the data into a class-oriented stratified split preserving the class distribution.
This class provides methods to obtain train and test splits for a given data set and split technique.
Class executing pseudo-random splits to enable multilabelcrossvalidation.