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Find maximum "k" ensuring that items with each cluster belong to only category. Each cluster would then be used as inputs to separate classification models. Building such smaller models helps in keeping things smaller and faster when a large number of categories/items makes training/testing very difficult

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abbas-gadhia/mahout-maximum-fully-exclusive-clusters

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mahout-maximum-fully-exclusive-clusters

Find maximum "k" ensuring that the items within each category are restricted to a single cluster. So for example, if there are 4 categories and "k" is 2, then one of the possible orientations of such a setup, would be 2 categories per cluster.

Each cluster would then be used as inputs to separate classification models.

Building such smaller models helps in keeping things smaller and faster when a large number of categories/items makes training/testing very difficult

For the motivation behind this project, [http://stackoverflow.com/questions/20950429/mahout-naive-bayes-model-very-slow] (http://stackoverflow.com/questions/20950429/mahout-naive-bayes-model-very-slow)

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Find maximum "k" ensuring that items with each cluster belong to only category. Each cluster would then be used as inputs to separate classification models. Building such smaller models helps in keeping things smaller and faster when a large number of categories/items makes training/testing very difficult

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