... random_state=1)>>> clf = MLPClassifier(random_state=1, max_iter=300).fit(X_train, y_train)>>> clf.predict_proba(X_test[:1]) array([[0.038..., 0.961...]])>>> clf.predict(X_test[:5, :]) array([1, 0, 1, 0, 1])>>>clf.score(X_test, y_test)0.8... Compare ...