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Chi-square test for feature extraction:
Chi-square test is used for categorical features in the dataset. We calculate the chi-square between each object and target and select the desired number of objects with the best chi-square values. It determines whether the relationship between two categorical variables in the sample will reflect their actual relationship in the population.
Chi-square score is given:
where —
Observed frequency = No. of observations of class
Expected frequency = No. of expected observations of class if there was no relationship between the feature and the target.
Python Implementation for Chi-Square Feature Selection:
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Exit :
Original feature number: 4 Reduced feature number: 2
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