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2011

Unsupervised and Supervised Learning Approaches Together for Microarray Analysis

8 years 4 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as a multiobjective optimization is used, which simultaneously optimizes two internal fuzzy cluster validity indices to yield a set of Pareto-optimal clustering solutions. In this regards, a new multiobjective differential evolution based fuzzy clustering technique has been proposed. Subsequently, for supervised learning, a fuzzy majority voting scheme along with support vector machine is used to integrate the clustering information from all the solutions in the resultant Pareto-optimal set. The performances of the proposed clustering techniques have been demonstrated on five publicly available benchmark microarray data sets. A detail comparison has been carried out with multiobjective genetic algorithm based fuzzy clustering, multiobjective differential evolution based fuzzy clustering, single objective versio...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa
Added 28 Aug 2011
Updated 28 Aug 2011
Type Journal
Year 2011
Where FUIN
Authors Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopadhyay, Dariusz Plewczynski
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