岭回归对波士顿房价进行预测
def linear3(): """ 岭回归对波士顿房价进行预测 :return: """ # 1)获取数据 boston = load_boston() print("特征数量:\n", boston.data.shape) # 2)划分数据集 x_train, x_test, y_train, y_test = train_test_split(boston.data, boston.target, random_state=22) # 3)标准化 transfer = StandardScaler() x_train = transfer.fit_transform(x_train) x_test = transfer.transform(x_test) # 4)预估器 # estimator = Ridge(alpha=0.5, max_iter=10000) # estimator.fit(x_train, y_train) # 保存模型 # joblib.dump(estimator, "my_ridge.pkl") # 加载模型 estimator = joblib.load("my_ridge.pkl") # 5)得出模型 print("岭回归-权重系数为:\n", estimator.coef_) print("岭回归-偏置为:\n", estimator.intercept_) # 6)模型评估 y_predict = estimator.predict(x_test) print("预测房价:\n", y_predict) error = mean_squared_error(y_test, y_predict) print("岭回归-均方误差为:\n", error) return None