29 lines
773 B
Python
29 lines
773 B
Python
# 使用sklearn.cluster库中的MeanShift类，对生成的二维模拟数据进行聚类。
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import matplotlib.pyplot as plt
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import numpy as np
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from sklearn.cluster import MeanShift, estimate_bandwidth
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from sklearn.datasets import make_blobs
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centers = [[1, 1], [-1, -1], [1, -1]]
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X, _ = make_blobs(n_samples=300, centers=centers, cluster_std=0.4)
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bandwidth = estimate_bandwidth(X, quantile=0.2, n_samples=300)
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ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
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ms.fit(X)
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labels = ms.labels_
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cluster_centers = ms.cluster_centers_
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plt.scatter(X[:, 0], X[:, 1], c=labels, s=50, cmap="viridis")
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plt.scatter(
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cluster_centers[:, 0],
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cluster_centers[:, 1],
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s=300,
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c="red",
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marker="*",
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edgecolor="k",
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)
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plt.title("Mean Shift Clustering")
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plt.show()
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