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- import matplotlib.pyplot as plt
- from sklearn.cluster import KMeans
- from sklearn.datasets import make_blobs
- def show_kmeans():
- # 生成测试样本
- n_samples = 1500
- random_state = 170
- x, y = make_blobs(n_samples=n_samples, random_state=random_state)
- # 聚类，指定聚类个数为3
- y_pred = KMeans(n_clusters=3, random_state=random_state).fit_predict(x)
- # 画图
- plt.subplot(221)
- plt.scatter(x[:, 0], x[:, 1], c=y_pred)
- plt.title("K-means")
- plt.show()
- if __name__ == '__main__':
- show_kmeans()
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