DICLENS: divisive clustering ensemble with automatic cluster number.

Clustering has a long and rich history in a variety of scientific fields. Finding natural groupings of a data set is a hard task as attested by hundreds of clustering algorithms in the literature. Each clustering technique makes some assumptions about the underlying data set. If the assumptions hold, good clusterings can be expected. It is hard, in some cases impossible, to satisfy all the assumptions. Therefore, it is beneficial to apply different clustering methods on the same data set, or the same method with varying input parameters or both. We propose a novel method, DICLENS, which combines a set of clusterings into a final clustering having better overall quality. Our method produces the final clustering automatically and does not take any input parameters, a feature missing in many existing algorithms. Extensive experimental studies on real, artificial, and gene expression data sets demonstrate that DICLENS produces very good quality clusterings in a short amount of time. DICLENS implementation runs on standard personal computers by being scalable, and by consuming very little memory and CPU.

Obtaining better quality final clustering by merging a collection of clusterings.

MOTIVATION: Clustering methods including k-means, SOM, UPGMA, DAA, CLICK, GENECLUSTER, CAST, DHC, PMETIS and KMETIS have been widely used in biological studies for gene expression, protein localization, sequence recognition and more. All these clustering methods have some benefits and drawbacks. We propose a novel graph-based clustering software called COMUSA for combining the benefits of a collection of clusterings into a final clustering having better overall quality. RESULTS: COMUSA implementation is compared with PMETIS, KMETIS and k-means. Experimental results on artificial, real and biological datasets demonstrate the effectiveness of our method. COMUSA produces very good quality clusters in a short amount of time. AVAILABILITY: http://www.cs.umb.edu/∼smimarog/comusa CONTACT: selim.mimaroglu@bahcesehir.edu.tr