13 lines
509 B
Python
13 lines
509 B
Python
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from sklearn.neural_network import MLPClassifier
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from sklearn.metrics import accuracy_score
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def random_state_fit(i, x_train, y_train, x_test, y_test, func):
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mlp = MLPClassifier(random_state=i, max_iter=4000, n_iter_no_change=10,
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activation=func, alpha=0.01, hidden_layer_sizes=[100, 100])
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mlp.fit(x_train, y_train)
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predictions = mlp.predict(x_test)
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acc_mlp = accuracy_score(y_test, predictions)
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print(f"Func {func} with accuracy {acc_mlp} \n")
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return acc_mlp
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