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- feature_ranking(F)
- Rank features in descending order according to t-score, the higher the t-score, the more important the feature is
- t_score(X, y)
- This function calculates t_score for each feature, where t_score is only used for binary problem
t_score = |mean1-mean2|/sqrt(((std1^2)/n1)+((std2^2)/n2)))
Input
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X: {numpy array}, shape (n_samples, n_features)
input data
y: {numpy array}, shape (n_samples,)
input class labels
Output
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F: {numpy array}, shape (n_features,)
t-score for each feature
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