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from sklearn import tree

TEXTURE_BUMPY = 0

TEXTURE_SMOOTH = 1

LABEL_APPLE = 0

LABEL_ORANGE = 1

LABELS = {

LABEL_APPLE: 'apple',

LABEL_ORANGE: 'orange',

}

def classify(to_classify):

features = [

[90, TEXTURE_BUMPY],

[140, TEXTURE_SMOOTH],

[130, TEXTURE_SMOOTH],

[150, TEXTURE_BUMPY],

[170, TEXTURE_BUMPY],

]

labels = [

LABEL_ORANGE,

LABEL_APPLE,

LABEL_APPLE,

LABEL_ORANGE,

LABEL_ORANGE

]

clf = tree.DecisionTreeClassifier()

clf = clf.fit(features, labels)

return clf.predict(to_classify)

def main():

to_classify = [

[160, TEXTURE_BUMPY],

[145, TEXTURE_BUMPY],

[120, TEXTURE_SMOOTH],

[100, TEXTURE_BUMPY],

]

decisions = classify(to_classify)

for decision in decisions:

print("It's a(n):", LABELS[decision])

if __name__ == '__main__':

main()