from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split from sklearn.neural_network import MLPClassifier ir = load_iris() X = ir.data y = ir.target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0) cl = MLPClassifier(solver="sgd",random_state=0,max_iter=10000) cl.fit(X_train, y_train) print ("識別率：", cl.score(X_test, y_test))
