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from sklearn.datasets import load_breast_cancer

from sklearn.model_selection import train_test_split

from sklearn.tree import DecisionTreeClassifier, plot_tree

from sklearn.metrics import accuracy_score

import matplotlib.pyplot as plt


X, y = load_breast_cancer(return_X_y=True)

Xt, Xs, yt, ys = train_test_split(X, y, test_size=0.2)

m = DecisionTreeClassifier().fit(Xt, yt)


print("Acc: %.2f%%" % (accuracy_score(ys, m.predict(Xs)) * 100))

print("Class:", ["Malignant", "Benign"][m.predict([Xs[0]])[0]])


plot_tree(m, filled=True); plt.show()



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