### 如何在 Silhouette 图表中添加 X 轴和 Y 轴标签 为了在 Silhouette 图表中添加 X 轴和 Y 轴标签，可以使用 `matplotlib` 库中的函数 `xlabel()` 和 `ylabel()` 来设置相应的轴标签。下面是一个完整的例子展示如何创建并标注 Silhouette 图表。 ```python import numpy as np import matplotlib.pyplot as plt from sklearn.metrics import silhouette_samples, silhouette_score from sklearn.cluster import KMeans # 假设已经有一个数据集X以及对应的簇分配labels n_clusters = 3 sample_silhouette_values = silhouette_samples(X, labels) fig, ax = plt.subplots(1, 1) y_lower = 10 for i in range(n_clusters): ith_cluster_silhouette_values = sample_silhouette_values[labels == i] ith_cluster_silhouette_values.sort() size_cluster_i = ith_cluster_silhouette_values.shape[0] y_upper = y_lower + size_cluster_i color = plt.cm.Spectral(float(i) / n_clusters) ax.fill_betweenx(np.arange(y_lower, y_upper), 0, ith_cluster_silhouette_values, facecolor=color, edgecolor=color, alpha=0.7) # Label the silhouette plots with their cluster numbers at the middle ax.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i)) # Compute the new y_lower for next plot y_lower = y_upper + 10 ax.set_title('Silhouette Plot') ax.set_xlabel('The silhouette coefficient values') # 设置X轴标签[^1] ax.set_ylabel('Cluster label') # 设置Y轴标签[^1] # The vertical line for average silhouette score of all the values avg_score = silhouette_score(X, labels) ax.axvline(x=avg_score, color="red", linestyle="--") plt.yticks([]) # Clear the yaxis labels / ticks plt.xticks([-0.1, 0, 0.2, 0.4, 0.6, 0.8, 1]) plt.show() ``` 通过上述代码片段，在