A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been shown to be more effective in finding clusters than some traditional algorithms such as kmeans. To perform clustering on large data sets, we implement various ways of approximating the dense similarity matrix, including nearest neighbors and the Nystrom method.
- Changes to previous version:
Initial Announcement on mloss.org.
Leave a comment
You must be logged in to post comments.