text_plain_output_1.png
from sklearn.tree import DecisionTreeClassifier

y_train.value_counts(normalize=True)

from sklearn.tree import DecisionTreeClassifier
clf = DecisionTreeClassifier(max_depth=20, criterion='entropy', random_state=42)
clf.fit(X_train, y_train)