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a general drawback of k-means. You have to select the k. In practice you try a range and see how well they summarize your data (e.g. leave one out cross validat
by tlarkworthy 12y ago
a general drawback of k-means. You have to select the k. In practice you try a range and see how well they summarize your data (e.g. leave one out cross validation).
You could do that here too, just have a range of k. If only there were a streaming leave-one-out cross validation for k-means to complement this approach ...
(it is possible to do this in a streaming style, see LWPR)
- michaelmior 12y agoI understand that's a drawback of k-means. I was just wondering if this was something that Spark solved natively. Looks like the answer is no for the time being. Thanks for the pointer to LWPR :)
- rxin 12y agoMaybe using BP-Means: http://arxiv.org/abs/1212.2126 http://arxiv.org/abs/1212.2126 K-Means without preset K.