Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling

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@InProceedings{2735,

• author = "Stephan M. Winkler and Michael Affenzeller and Gabriel K. Kronberger and Michael Kommenda and Stefan Wagner and Witold Jacak and Herbert Stekel",
• title = "Analysis of Selected Evolutionary Algorithms in Feature Selection and Parameter Optimization for Data Based Tumor Marker Modeling",
• booktitle = "Computer Aided Systems Theory, EUROCAST 2011",
• year = "2012",
• editor = "Roberto Moreno-Diaz and Franz Pichler and Alexis Quesada-Arencibia",
• volume = "6927",
• series = "Lecture Notes in Computer Science",
• pages = "335--342",
• month = feb,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-27549-4",
• URL = "https://link.springer.com/chapter/10.1007/978-3-642-27549-4_43",
• DOI = "doi:10.1007/978-3-642-27549-4_43",
• abstract = "In this paper we report on the use of evolutionary algorithms for optimizing the identification of classification models for selected tumour markers. Our goal is to identify mathematical models that can be used for classifying tumor marker values as normal or as elevated; evolutionary algorithms are used for optimizing the parameters for learning classification models. The sets of variables used as well as the parameter settings for concrete modelling methods are optimized using evolution strategies and genetic algorithms. The performance of these algorithms is analysed as well as the population diversity progress. In the empirical part of this paper we document modeling results achieved for tumour markers CA 125 and CYFRA using a medical data base provided by the Central Laboratory of the General Hospital Linz; empirical tests are executed using HeuristicLab.",

}

Genetic Programming entries for Stephan M Winkler Michael Affenzeller Gabriel Kronberger Michael Kommenda Stefan Wagner Witold Jacak Herbert Stekel

Citations