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from sklearn.neural_network import MLPClassifier
X = [[0., 0.], [1., 1.],[2.,2.],[3.,3.],[0., 1.]]
y = [0, 1, 2, 3, 4]
#Class MLPClassifier implements a multi-layer perceptron (MLP) algorithm
#
clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 4), random_state=1)
clf.fit(X, y) 


clf.predict([[3., 3.], [0., 1.]])

clf.predict_proba([[3., 3.], [0., 1.]])



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