Computer Science – Artificial Intelligence
Scientific paper
2007-01-03
Computer Science
Artificial Intelligence
15 pages
Scientific paper
In this paper, the traditional k-modes clustering algorithm is extended by weighting attribute value matches in dissimilarity computation. The use of attribute value weighting technique makes it possible to generate clusters with stronger intra-similarities, and therefore achieve better clustering performance. Experimental results on real life datasets show that these value weighting based k-modes algorithms are superior to the standard k-modes algorithm with respect to clustering accuracy.
Deng Shengchun
He Zengyou
Xu Xaiofei
No associations
LandOfFree
Attribute Value Weighting in K-Modes Clustering does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Attribute Value Weighting in K-Modes Clustering, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Attribute Value Weighting in K-Modes Clustering will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-563648