K均值用于对具有许多零值的数据进行聚类吗? [英] Is K-means for clustering data with many zero values?

问题描述

我需要对一个主要包含零值的矩阵进行聚类... K均值是否适合此类数据，还是需要考虑使用其他算法?

I need to cluster a matrix which contains mostly zeros values...Is K-means appropriate for these kind of data or do I need to consider a different algorithm?

推荐答案

否.原因是平均值对稀疏数据不明智.所得的平均向量将具有与实际数据完全不同的特征；他们最终往往会彼此之间比实际文档更相似！

No. The reason is that the mean is not sensible on sparse data. The resulting mean vectors will have very different characteristics than your actual data; they will often end up being more similar to each other than to actual documents!

有些改进可以改善稀疏数据的k均值，例如球形 k均值.

There are some modifications that improve k-means for sparse data such as spherical k-means.

但在很大程度上，此类数据的k均值只是一种粗略的试探法.结果并非完全没有用，但是它们也不是您可以做到的最好的结果.它有效，但不是偶然，而是偶然的.

But largely, k-means on such data is just a crude heuristic. The results aren't entirely useless, but they are not the best that you can do either. It works, but by chance, not by design.

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