museotoolbox.ai.SuperLearner.fit

SuperLearner.fit(X, y, group=None, standardize=True, cv=None, scoring='accuracy', refit=True, **gridSearchCVParams)[source]

Fit model from array.

Parameters

  • X (np.ndarray.) – Array with values of each label variable.

  • y (np.ndarray.) – Array with labels only.

  • group (str or False.) – If you use a cross-validation which needs group-splitting.

  • strandardize (Bool, default True.) – If True, will standardize features by removing the mean and scaling to unit variance.

  • cv (Cross-Validation or int or None. Default None.) – if cv, choose one from cross_validation. if int, uses museotoolbox.cross_validation.RandomStratifiedKFold with K = the int value.