Centre for Modeling and Simulation
Savitribai Phule Pune University All Models Are False, Some Are Useful

Technical Report CMS-TR-20120509


Title Biogeography-Based Informative Gene Selection and Cancer Classification Using SVM and Random Forests
Author/s Sarvesh Nikumbh
Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India


Shameek Ghosh
Centre for Development of Advanced Computing, Pune, INDIA


and

V.K. Jayaraman
Centre for Development of Advanced Computing, Pune, INDIA
Abstract Microarray cancer gene expression data comprise of very high dimensions. Reducing the dimensions helps in improving the overall analysis and classification performance. We propose two hybrid techniques, Biogeography – based Optimization – Random Forests (BBO – RF) and BBO – SVM (Support Vector Machines) with gene ranking as a heuristic, for microarray gene expression analysis. This heuristic is obtained from information gain filter ranking procedure. The BBO algorithm generates a population of candidate subset of genes, as part of an ecosystem of habitats, and employs the migration and mutation processes across multiple generations of the population to improve the classification accuracy. The fitness of each gene subset is assessed by the classifiers – SVM and Random Forests. The performances of these hybrid techniques are evaluated on three cancer gene expression datasets retrieved from the Kent Ridge Biomedical datasets collection and the libSVM data repository. Our results demonstrate that genes selected by the proposed techniques yield classification accuracies comparable to previously reported algorithms.
Keywords
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Citing This Document Sarvesh Nikumbh, Shameek Ghosh, and V.K. Jayaraman , Biogeography-Based Informative Gene Selection and Cancer Classification Using SVM and Random Forests . Technical Report CMS-TR-20120509 of the Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411007, India (2012); available at http://cms.unipune.ernet.in/reports/.
Notes, Published Reference, Etc. Published in the Proceedings of the IEEE World Congress on Evolutionary Computation, 2012, held at Brisbane, Australia; more information available here.
Contact sarvesh AT cms.unipune.ernet.in
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