[MAHOUT-29] Gibb's sampling implementation

• Type: New Feature
• Status: Closed
• Priority: Major
• Resolution: Won't Fix
• Assignee: Unassigned
• Reporter: Isabel Drost-Fromm
• Created: 08/Apr/08 14:15
• Updated: 21/May/11 03:27
• Resolved: 18/Nov/09 12:03

Description

Copied over from original issue:

> EM clustering can also be changed very slightly by assigning points to single clusters chosen at random according to the probability of membership. This
> turns EM clustering into Gibb's sampling. The important property that is changed is that you now can sample over the distribution of possible samplings
> which can be very important if some parts of your data are well defined and some parts not so well defined.

Issue Links

• is part of: MAHOUT-4 Simple prototype for Expectation Maximization (EM)