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import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.cluster import KMeans

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iris = datasets.load_iris()
X = iris.data
y = iris.target

# 浣跨敤KMeans绠楁硶杩涜鑱氱被
kmeans = KMeans(n_clusters=3)
kmeans.fit(X)
y_kmeans = kmeans.predict(X)

# 灏嗚仛绫荤粨鏋滃彲瑙嗗寲
plt.scatter(X[:, 0], X[:, 1], c=y_kmeans, cmap='viridis')
centers = kmeans.cluster_centers_
plt.scatter(centers[:, 0], centers[:, 1], c='red', s=200, alpha=0.5)
plt.xlabel('Sepal length')
plt.ylabel('Sepal width')
plt.show()

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