ITMO_FS.filters.univariate.spearman_corr

ITMO_FS.filters.univariate.spearman_corr(X, y)

Calculates spearman correlation for each feature. Spearman’s correlation assesses monotonic relationships (whether linear or not). If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other.

Parameters:

• X (numpy array, shape (n_samples, n_features)) – The input samples.
• y (numpy array, shape (n_samples, )) – The classes for the samples.

Returns:

Return type:

Score for each feature as a numpy array, shape (n_features, )

See also

https()

//en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient

Examples

>>> import sklearn.datasets as datasets
>>> from ITMO_FS.filters.univariate import spearman_corr
>>> X, y = datasets.make_classification(n_samples=200, n_features=7, shuffle=False)
>>> scores = spearman_corr(X, y)
>>> print(scores)