[ https://issues.apache.org/jira/browse/MAHOUT-153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rohini Uppuluri updated MAHOUT-153: ----------------------------------- Comment: was deleted (was: Hi, This is the patch for creating random farthest cluster initialization. This does not have junit test cases yet. Thanks, -Rohini) > Implement kmeans++ for initial cluster selection in kmeans > ---------------------------------------------------------- > > Key: MAHOUT-153 > URL: https://issues.apache.org/jira/browse/MAHOUT-153 > Project: Mahout > Issue Type: New Feature > Components: Clustering > Affects Versions: 0.2 > Environment: OS Independent > Reporter: Panagiotis Papadimitriou > Assignee: Ted Dunning > Fix For: 0.4 > > Attachments: Mahout-153.patch, MAHOUT-153_RandomFarthest.patch > > Original Estimate: 336h > Remaining Estimate: 336h > > The current implementation of k-means includes the following algorithms for > initial cluster selection (seed selection): 1) random selection of k points, > 2) use of canopy clusters. > I plan to implement k-means++. The details of the algorithm are available > here: http://www.stanford.edu/~darthur/kMeansPlusPlus.pdf. > Design Outline: I will create an abstract class SeedGenerator and a subclass > KMeansPlusPlusSeedGenerator. The existing class RandomSeedGenerator will > become a subclass of SeedGenerator. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.