最小二乘法线性回归

def solve():
    from sklearn.datasets import load_diabetes
    import numpy as np
    import matplotlib.pyplot as plt
    diabetes = load_diabetes()
    X = diabetes.data[:, ____]
    y = diabetes.target
    X_mean = np.mean(____)
    y_mean = np.mean(____)
    numerator = np.sum((____) * (____))
    denominator = np.sum((____) ** ____)
    slope = numerator / denominator
    intercept = y_mean - slope * X_mean
    y_pred = slope * X + intercept
    ss_res = np.sum((____) ** ____)
    ss_tot = np.sum((____) ** ____)
    r_squared = ____ - (____)
    print(____)
    print(____)
    print(____)
    plt.figure(figsize=(____, ____))
    plt.scatter(____)
    plt.plot(____)
    plt.xlabel(____)
    plt.ylabel(____)
    plt.title(____)
    plt.legend()
    plt.grid(____)
    plt.show()