如何使用matplotlib定义特征重要性分数中从max到min的值的顺序？

import numpy as np
import matplotlib.pyplot as plt

# 假设有5个特征和对应的重要性分数
feature_names = ['Feature A', 'Feature B', 'Feature C', 'Feature D', 'Feature E']
feature_scores = [0.8, 0.6, 0.9, 0.7, 0.5]

# 对特征重要性分数进行排序
sorted_indices = np.argsort(feature_scores)

# 反转排序后的索引值
sorted_indices = np.flip(sorted_indices)

# 根据排序后的索引值获取特征名称和重要性分数
sorted_names = [feature_names[i] for i in sorted_indices]
sorted_scores = [feature_scores[i] for i in sorted_indices]

# 创建水平条形图
plt.barh(range(len(sorted_names)), sorted_scores, align='center')
plt.yticks(range(len(sorted_names)), sorted_names)
plt.xlabel('Feature Importance Score')
plt.ylabel('Feature Name')
plt.title('Feature Importance')

# 显示图形
plt.show()