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Posted to dev@mahout.apache.org by "Dave DeBarr (JIRA)" <ji...@apache.org> on 2013/11/05 23:56:17 UTC

[jira] [Created] (MAHOUT-1351) Adding DenseVector support to AbstractCluster

Dave DeBarr created MAHOUT-1351:
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             Summary: Adding DenseVector support to AbstractCluster
                 Key: MAHOUT-1351
                 URL: https://issues.apache.org/jira/browse/MAHOUT-1351
             Project: Mahout
          Issue Type: Improvement
          Components: Clustering
    Affects Versions: 0.8
            Reporter: Dave DeBarr
            Priority: Minor
             Fix For: 0.9


This improvement reduces runtime by 80% when performing k-means clustering of Scale Invariant Feature Transform (SIFT) descriptors to derive visual words for computer vision.  Unlike sparse document vectors, SIFT descriptors are dense.  This improvement involves updating the org.apache.mahout.clustering.AbstractCluster(Vector point, int id2) constructor to use "point.clone()" instead of "new RandomAccessSparseVector(point)" for creating the centroid.  Also added testKMeansSeqJobDenseVector() test for DenseVector processing.




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