Lasso回归

def solve():
    from sklearn.datasets import load_diabetes
    from sklearn.linear_model import Lasso
    from sklearn.model_selection import train_test_split
    import matplotlib.pyplot as plt
    import numpy as np
    diabetes = load_diabetes()
    X_train, X_test, y_train, y_test = train_test_split(____)
    lasso = Lasso(____)
    lasso.fit(____)
    print(____)
    for name, coef in zip(____):
        print(____)
    n_nonzero = np.sum(____)
    print(____)
    plt.figure(figsize=(____, ____))
    plt.bar(range(len(____)), lasso.coef_)
    plt.xticks(range(len(____)), diabetes.feature_names, rotation=____)
    plt.xlabel(____)
    plt.ylabel(____)
    plt.title(____)
    plt.axhline(____, color='____', linewidth=____)
    plt.grid(____)
    plt.tight_layout()
    plt.show()