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eatp ... main

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import numpy as np
from sklearn.cluster import KMeans
import time
import
# 生成随机数据
np.random.seed(0)
X = np.random.rand(10000, 10)
# 设置要测试的聚类数目
n_clusters = 3
# 创建K均值聚类模型
kmeans = KMeans(n_clusters=n_clusters)
# 运行K均值聚类算法
start_time = time.time()
kmeans.fit(X)
end_time = time.time()
# 输出聚类结果和算法执行时间
print("聚类中心坐标:")
print(kmeans.cluster_centers_)
print("\n算法执行时间: {:.4f}".format(end_time - start_time))
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