Top Scoring Pair Decision Tree for Gene Expression Data Analysis

Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 696)

Abstract

Classification problems of microarray data may be successfully performed with approaches by human experts which are easy to understand and interpret, like decision trees or Top Scoring Pairs algorithms. In this chapter, we propose a hybrid solution that combines the above-mentioned methods. An application of presented decision trees, which splits instances based on pairwise comparisons of the gene expression values, may have considerable potential for genomic research and scientific modeling of underlying processes. We have compared proposed solution with the TSP-family methods and decision trees on 11 public domain microarray datasets and the results are promising.

Keywords

Leukemia 

Notes

Acknowledgements

This work was supported by the grant W/WI/5/08 from Białystok Technical University.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Faculty of Computer ScienceBialystok University of TechnologyBialystokPoland

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