scikit decision tree classifier gini criterion
from sklearn.tree import DecisionTreeClassifier from sklearn import metrics # Max depth Decision tree classifier using gini criterion clf_gini_max = DecisionTreeClassifier(random_state=50, criterion='gini', max_depth=None) clf_gini_max = clf_gini_max.fit(X_train,Y_train) Y_pred = clf_gini_max.predict(X_test) training_accuracy = clf_gini_max.score(X_train,Y_train) testing_accuracy = clf_gini_max.score(X_test,Y_test) print(training_accuracy) print(testing_accuracy)
