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arXiv · 1512.07548

k-Means Clustering Is Matrix Factorization

Christian Bauckhage
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Abstract

We show that the objective function of conventional k-means clustering can be expressed as the Frobenius norm of the difference of a data matrix and a low rank approximation of that data matrix. In short, we show that k-means clustering is a matrix factorization problem. These notes are meant as a reference and intended to provide a guided tour towards a result that is often mentioned but seldom made explicit in the literature.

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Christian Bauckhage. 2015-12-23. k-Means Clustering Is Matrix Factorization. https://arxiv.org/abs/1512.07548

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