from sklearn.neural_network import MLPClassifier clf = MLPClassifier(solver='lbfgs',alpha=1e-5,max_iter=200,\ activation='relu',hidden_layer_sizes=(10,30,10),\ random_state=1, shuffle=True) clf.fit(XA,yA) yP = clf.predict(XB) assess(yP)