1.选出k值,随机出k个起始质心点。
2.分别计算每个点和k个起始质点之间的距离,就近归类。
3.最终中心点集可以划分为k类,分别计算每类中新的中心点。
4.重复2,3步骤对所有点进行归类,如果当所有分类的质心点不再改变,则最终收敛。
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the K value was selected and K initial centroid points were randomly out.
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calculate the distance between each point and the starting point of K, and then classify them near.
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the final center point set can be divided into k classes, and the new center points in each class are calculated respectively.
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repeat 2,3 steps to classify all points, and eventually converge if the centroid points of all categories are no longer changed.