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Chisquare test for feature extraction:
Chisquare test is used for categorical features in the dataset. We calculate the chisquare between each object and target and select the desired number of objects with the best chisquare values. It determines whether the relationship between two categorical variables in the sample will reflect their actual relationship in the population.
Chisquare 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 ChiSquare Feature Selection:

Exit :
Original feature number: 4 Reduced feature number: 2
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