15 lines
447 B
Python
15 lines
447 B
Python
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from sklearn.neural_network import MLPRegressor
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from scores import MAPE
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def random_state_fit(i, x, y, x_test, y_test):
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mlr = MLPRegressor(random_state=i, max_iter=2000, n_iter_no_change=20,
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activation='relu', alpha=0.01, hidden_layer_sizes=[20, 20], tol=0.0000001)
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mlr.fit(x, y)
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y_pred = mlr.predict(x_test)
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acc = 100 - MAPE(y_test, y_pred)
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print('random state', i, "\naccuracy", acc)
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return acc
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