Convergence Properties of the K-means Algorithms L Eon Bottou
نویسنده
چکیده
This paper studies the convergence properties of the well known K Means clustering algorithm The K Means algorithm can be de scribed either as a gradient descent algorithm or by slightly extend ing the mathematics of the EM algorithm to this hard threshold case We show that the K Means algorithm actually minimizes the quantization error using the very fast Newton algorithm
منابع مشابه
Convergence Properties of the K-Means Algorithms
This paper studies the convergence properties of the well known K-Means clustering algorithm. The K-Means algorithm can be described either as a gradient descent algorithm or by slightly extending the mathematics of the EM algorithm to this hard threshold case. We show that the K-Means algorithm actually minimizes the quantization error using the very fast Newton algorithm.
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تاریخ انتشار 2007