I have extracted a set of features for a classification task and I used the SVM classifier. How can I find the top k predictive features and their discriminative power (chi square) value?


Here is a tutorial on the website of scikit-learn that shows you how to compute chi².

Copying from the mentioned website:

>>> from sklearn.datasets import load_iris
>>> from sklearn.feature_selection import SelectKBest
>>> from sklearn.feature_selection import chi2
>>> iris = load_iris()
>>> X, y = iris.data, iris.target
>>> X.shape
(150, 4)
>>> X_new = SelectKBest(chi2, k=2).fit_transform(X, y)
>>> X_new.shape
(150, 2)

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