%matplotlib inline
from sklearn.tree import DecisionTreeClassifier
from sklearn.datasets import load_breast_cancer
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import mglearn
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split

cancer = load_breast_cancer()

X_train, X_test, y_train, y_test = train_test_split(
 cancer.data, cancer.target, stratify=cancer.target, random_state=42)

tree = DecisionTreeClassifier(random_state=0)
tree.fit(X_train, y_train)

print("Accuracy on training set: {:.3f}".format(tree.score(X_train, y_train)))
print("Accuracy on test set: {:.3f}".format(tree.score(X_test, y_test)))