scikit-learn中的聚类算法:http://scikit-learn.org/stable/modules/clustering.html scikit-learn K-Means文档:http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html K-Means算法的基本思想是初始随机给定K个簇中心,按照最邻近原则把待分类样本点分到各个簇。然后按平均法重新计算各个簇的...
X, y = make_blobs(n_samples=400, centers=4, cluster_std=0.60, random_state=0) # kmeans clustering kmeans = KMeans(4, random_state=0) kmeans.fit(X) # 训练模型 labels = kmeans.predict(X) # 预测分类 plt.scatter(X[:, 0], X[:, 1], c=labels, s=40, cmap='viridis') plt....