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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