Mutual Information for Regression

mutual_info_regression.py

from sklearn.feature_selection import mutual_info_regression  
from sklearn.feature_selection import SelectKBest
selector = SelectKBest(mutual_info_regression, k=10)
X_train_new = selector.fit_transform(X_train, y_train)  #Applying transformation to the training set
#to get names of the selected features
mask = selector.get_support()     # Output   array([False, False,  True,  True,  True, False ....])

print(selector.scores_)     #Output array([0.16978127, 0.01829886, 0.45461366, 0.55126343, 0.66081217, 0.27715287 ....])

new_features = X_train.columns[mask]
print(new_features)   #Output Index(['wheelbase', 'carlength', 'carwidth', 'curbweight', 'enginesize','boreratio', 'horsepower', 'citympg', 'highwaympg', 'fuelsystem_2bbl'],dtype='object')
print(train.shape)  #Output (143, 10)