ITMO_FS.filters.univariate.fit_criterion_measure

ITMO_FS.filters.univariate.fit_criterion_measure(x, y)

Calculate the FitCriterion score for features. Bigger values mean more important features.

Parameters:

• x (array-like, shape (n_samples, n_features)) – The training input samples.
• y (array-like, shape (n_samples,)) – The target values.

Returns:

array-like, shape (n_features,)

Return type:

feature scores

See also

https()

//core.ac.uk/download/pdf/191234514.pdf

Examples

>>> from ITMO_FS.filters.univariate import fit_criterion_measure
>>> import numpy as np
>>> x = np.array([[1, 2, 4, 1, 1], [2, 2, 2, 1, 2], [3, 5, 1, 1, 4],
... [1, 1, 1, 1, 4], [2, 2, 2, 1, 5]])
>>> y = np.array([1, 2, 3, 1, 2])
>>> fit_criterion_measure(x, y)
array([1. , 0.8, 0.8, 0.4, 0.6])