弹性网络

def solve():
    from sklearn.datasets import load_diabetes
    from sklearn.linear_model import ElasticNet
    from sklearn.model_selection import train_test_split, GridSearchCV
    import numpy as np
    diabetes = load_diabetes()
    X_train, X_test, y_train, y_test = train_test_split(____)
    param_grid = {'____': [____, ____, ____], '____': [____, ____, ____]}
    elastic = ElasticNet()
    grid_search = GridSearchCV(____)
    grid_search.fit(____)
    print(____)
    print(____)
    best_model = grid_search.best_estimator_
    print(____)
    for name, coef in zip(____):
        print(____)