High-performance document clustering systems enable similar documents to automatically self-organize into groups. In the past, the large amount of computational time needed to clu...
G. Adam Covington, Charles L. G. Comstock, Andrew ...
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
—In this paper, we have modified a constrained clustering algorithm to perform exploratory analysis on gene expression data using prior knowledge presented in the form of constr...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...