回归评估指标可视化

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    from sklearn.linear_model import LinearRegression
    from sklearn.metrics import mean_squared_error, r2_score
    from sklearn.model_selection import train_test_split
    df = pd.read_csv(____).head(____)
    X = df.drop(____); y = df["____"]
    X_train, X_test, y_train, y_test = train_test_split(____)
    lr = LinearRegression().fit(____)
    y_pred = lr.predict(____)
    plt.scatter(____)
    plt.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "____")
    plt.xlabel(____); plt.ylabel(____); plt.title(____)
    plt.show()
    print(____)