bqlearn.model_selection.BiqualityCrossValidator

class bqlearn.model_selection.BiqualityCrossValidator(cv=None)

Biquality cross-validator.

In the Biquality Data setup, cross-validators split only trusted data. All untrusted samples are present in each training splits and test sets contain only trusted samples.

The sample_quality is provided through the groups argument of the split() method.

Parameters:

cvint, cross-validation generator or an iterable, default=None

Determines the cross-validation splitting strategy. Possible inputs for cv are: - None, to use the default 5-fold cross validation, - integer, to specify the number of folds. - CV splitter, - An iterable that generates (train, test) splits as arrays of indices.

For integer/None inputs, StratifiedKFold is used.

Methods

get_n_splits
split