K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset

Details K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset

2005-09-13

arxiv.org/abs/cs/0509033v1

Computer Science

Artificial Intelligence

11 pages

Scientific paper

Clustering categorical data is an integral part of data mining and has attracted much attention recently. In this paper, we present k-histogram, a new efficient algorithm for clustering categorical data. The k-histogram algorithm extends the k-means algorithm to categorical domain by replacing the means of clusters with histograms, and dynamically updates histograms in the clustering process. Experimental results on real datasets show that k-histogram algorithm can produce better clustering results than k-modes algorithm, the one related with our work most closely.

Affiliated with

Also associated with

No associations

Rating

K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset 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 K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-703536