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import numpy as np

from sklearn import tree

from sklearn.datasets import load_iris

def main():

iris = load_iris()

print(iris.feature_names)

print(iris.target_names)

# print(iris.data[0])

# print(iris.target[0])

test_idx = [0, 50, 100]

train_target = np.delete(iris.target, test_idx)

train_data = np.delete(iris.data, test_idx, axis=0)

test_target = iris.target[test_idx]

test_data = iris.data[test_idx]

# print(test_target)

# print(test_data)

clf = tree.DecisionTreeClassifier()

clf.fit(train_data, train_target)

print('actual:', test_target)

print('predicted:', clf.predict(test_data))

if __name__ == '__main__':

main()