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Vaijanath N. Rao commented on MAHOUT-173: ----------------------------------------- Hi Ted, Either one can use the Mahout-228 patch or just the lucene text vectorization already in there. After that it looks more likley to run K-means. > Implement clustering of massive-domain attributes > ------------------------------------------------- > > Key: MAHOUT-173 > URL: https://issues.apache.org/jira/browse/MAHOUT-173 > Project: Mahout > Issue Type: New Feature > Components: Clustering > Affects Versions: 0.2 > Reporter: Matias Bjørling > Priority: Trivial > Fix For: 0.3 > > Original Estimate: 30h > Remaining Estimate: 30h > > Implement the Clustering algorithm described in "A Framework for Clustering > Massive-Domain Data Streams" by Chary C. Aggarwal. > Steps: > 1. Implement baseline solution to compare solutions. > 2. Figure out how to implement the loading of clustering by looking at the > k-means implementation. > 3. Implement Count-Min sketch algorithm for each cluster. > 4. Find out how to give the user the power to choose the distance function > for the input data ( Maybe already possible? ) -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.