文件名称:kmeans-image-segmentation

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K-means算法是一种动态聚类方法,这种方法先选择若干样本作为聚类的中心,在按某种聚类准则(通常采用最小距离原则)使各种样本向各个中心积聚,从而得到初始的分类,然后,判断分类的合理性,如果不合理,就修改分类,如此反复的修改聚类的迭代运算,直到合理为止。-K-means algorithm is a dynamic clustering method, this method, select the number of samples as a cluster center in the cluster by some criteria (usually the principle of minimum distance) to the centers to the accumulation of a variety of samples, resulting in the initial classification, then determine the classification is reasonable, if unreasonable, to modify the classification, so repeatedly modified clustering iteration, until a reasonable date.
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kmeans-image-segmentation\kmeans.m

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kmeans-image-segmentation

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