We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the a...
We explore the idea of evidence accumulation for combining the results of multiple clusterings. Initially, n d-dimensional data is decomposed into a large number of compact cluste...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...