首先,使用fit方法将标准化器适配到数据上,并打印出了每个特征的均值和方差。然后,使用transform方法对数据进行转换,将标准化后的数据保存到变量z中。...= Lasso(alpha=1.0, max_iter=1000)
las.fit(X_train, Y_train)
print(las.coef_, las.intercept_) #训练模型后,...% las.score(X_test, Y_test), end='')
print("测试集MSE:%f" % mean_squared_error( Y_test, las.predict(X_test...= Lasso(alpha=1.0, max_iter=1000)
las.fit(X_train_pf, Y_train)
print(las.coef_, las.intercept_) #模型的系数和截距...mean_squared_error(Y_train, las.predict(X_train_pf)))
print("测试集R方:%f," % las.score(X_test_pf, Y_test