Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{czajkowski:2013:EuroGP,

• author = "Marcin Czajkowski and Marek Kretowski",
• title = "Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis",
• booktitle = "Proceedings of the 16th European Conference on Genetic Programming, EuroGP 2013",
• year = "2013",
• month = "3-5 " # apr,
• editor = "Krzysztof Krawiec and Alberto Moraglio and Ting Hu and A. Sima Uyar and Bin Hu",
• series = "LNCS",
• volume = "7831",
• publisher = "Springer Verlag",
• address = "Vienna, Austria",
• pages = "229--240",
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming, evolutionary algorithms, decision tree, top-scoring pair, classification, gene expression, micro-array",
• isbn13 = "978-3-642-37206-3",
• DOI = "doi:10.1007/978-3-642-37207-0_20",
• abstract = "Extracting knowledge from gene expression data is still a major challenge. Relative expression algorithms use the ordering relationships for a small collection of genes and are successfully applied for micro-array classification. However, searching for all possible subsets of genes requires a significant number of calculations, assumptions and limitations. In this paper we propose an evolutionary algorithm for global induction of top-scoring pair decision trees. We have designed several specialised genetic operators that search for the best tree structure and the splits in internal nodes which involve pairwise comparisons of the gene expression values. Preliminary validation performed on real-life micro-array datasets is promising as the proposed solution is highly competitive to other relative expression algorithms and allows exploring much larger solution space.",
• notes = "Part of \cite{Krawiec:2013:GP} EuroGP'2013 held in conjunction with EvoCOP2013, EvoBIO2013, EvoMusArt2013 and EvoApplications2013",

}

Genetic Programming entries for Marcin Czajkowski Marek Kretowski

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