层次聚类模拟数据

import numpy as np
from sklearn.preprocessing import StandardScaler
import scipy.cluster.hierarchy as shc
import matplotlib.pyplot as plt
np.random.seed(2)
X = np.random.randn(50, 2)
X[:25, 0] += 3
X[:25, 1] -= 4
scaler = StandardScaler()
X_scaled = scaler.fit_transform(X)
plt.figure(figsize=(10, 7))
dend = shc.dendrogram(shc.linkage(X_scaled, method='ward'))
plt.axhline(y=7, c='red', linestyle='--')
plt.title('层次聚类树状图')
plt.xlabel('样本索引')
plt.ylabel('距离')
plt.show()