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30 lines
488 B
Python
30 lines
488 B
Python
from sklearn.neural_network import MLPClassifier
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X = [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
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y = [0, 1, 0, 0]
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clf = MLPClassifier(
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solver="lbfgs", alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
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)
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clf.fit(X, y)
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test = [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
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Y = clf.predict(test)
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def wrapper(Y):
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"""
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>>> wrapper(Y)
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[0, 0, 1]
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"""
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return list(Y)
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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