如何在Python中可视化多维集群？

import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.datasets import make_blobs
from sklearn.cluster import KMeans

# 生成多维数据
X, y = make_blobs(n_samples=300, centers=4, cluster_std=0.60, random_state=0)

# 使用K-means进行聚类
kmeans = KMeans(n_clusters=4)
kmeans.fit(X)
y_kmeans = kmeans.predict(X)

# 使用Matplotlib绘制散点图
plt.figure(figsize=(10, 6))
plt.scatter(X[:, 0], X[:, 1], c=y_kmeans, s=50, cmap='viridis')
centers = kmeans.cluster_centers_
plt.scatter(centers[:, 0], centers[:, 1], c='red', s=200, alpha=0.5)
plt.title('K-means Clustering')
plt.xlabel('Feature 1')
plt.ylabel('Feature 2')
plt.show()

# 使用Seaborn绘制热力图
plt.figure(figsize=(10, 6))
sns.heatmap(X.corr(), annot=True, cmap='coolwarm')
plt.title('Heatmap of Correlation Matrix')
plt.show()