绘制特征重要性图

def solve():
    import matplotlib
    matplotlib.use('Agg')
    import matplotlib.pyplot as plt
    from sklearn.datasets import load_iris
    from sklearn.ensemble import RandomForestClassifier
    import numpy as np
    iris = load_iris()
    X = iris.data
    y = iris.target
    model = RandomForestClassifier(n_estimators=100, random_state=42).fit(X, y)
    importances = model.feature_importances_
    indices = np.argsort(importances)[::-1]
    plt.figure(figsize=(8, 5))
    plt.bar(range(4), importances[indices])
    plt.xticks(range(4), [iris.feature_names[i] for i in indices], rotation=45)
    plt.title('Feature Importances')
    plt.tight_layout()
    plt.show()
    print(f'{importances.sum():.4f}')