Hantao Chen , South China University of Technology, Guangzhou
Jane You , Hong Kong Polytechnic University, Hong Kong
Zhiwen Yu , South China University of Technology, Guangzhou and Hong Kong Polytechnic University, Hong Kong
Le Li , South China University of Technology, Guangzhou
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2013.59
In order to further improve the performance of tumor clustering from bio-molecular data, we introduce the fuzzy theory into the cluster ensemble framework for tumor clustering from bio-molecular data, and propose four kinds of hybrid fuzzy cluster ensemble frameworks, named as HFCEF-I, HFCEF-II, HFCEF-III and HFCEF-IV respectively, to identify samples which belong to different types of cancers. The difference between HFCEF-I and HFCEF-II is that they adopt different ensemble generator approaches to generate a set of fuzzy matrices in the ensemble. Specifically, HFCEF-I applies the affinity propagation algorithm (AP) to perform clustering on the sample dimension, and generates a set of fuzzy matrices in the ensemble based on the fuzzy membership function and base samples selected by AP. HFCEF-II adopts AP to perform clustering on the attribute dimension, generates a set of subspaces, and obtains a set of fuzzy matrices in the ensemble by performing fuzzy c-means on subspaces. Compared with HFCEF-I and HFCEF-II, HFCEF-III and HFCEF-IV consider the characteristics of HFCEF-I and HFCEF-II. HFCEF-III combines HFCEF-I and HFCEF-II in a serial way, while HFCEF-IV integrates HFCEF-I and HFCEF-II in a concurrent way.
Health, Computer Applications, Life and Medical Sciences, Biology and genetics
Hantao Chen, Jane You, Zhiwen Yu, Le Li, "Hybrid Fuzzy Cluster Ensemble Framework for Tumor Clustering from Bio-molecular Data", IEEE/ACM Transactions on Computational Biology and Bioinformatics, , no. 1, pp. 1, PrePrints PrePrints, doi:10.1109/TCBB.2013.59