museotoolbox.ai.SequentialFeatureSelection.fit

SequentialFeatureSelection.fit(X, y, group=None, cv=5, scoring='accuracy', standardize=True, max_features=False, n_jobs=1, **kwargs)

Parameters

• X (np.ndarray) – shape of np.ndarray is (n_size,n_bands).

• y (np.ndarray) – Size of X.shape[0].

• group (None, optional) – group for cross-validation

• cv (int, or cross_validation method, optional (default=5)) – Default will use

• scoring (str or class, optional (default='accuracy')) – default is ‘accuracy’. See sklearn.metrics.make_scorer from scikit-learn.

• standardize (optional) – Default True.

• max_features (int or bool.) – Default False, if value int.

• n_jobs (int.) – Number of job to compute cross-validation.