In this paper we report on the use of evolutionary algorithms for optimizing the identification of classification models for selected tumor 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 modeling methods are optimized using evolution strategies and genetic algorithms. The performance of these algorithms is analyzed as well as the population diversity progress.
|Number of pages||4|
|Publication status||Published - 2011|
|Event||13th International Conference on Computer Aided Systems Theory EUROCAST 2011 - Las Palmas, Spain|
Duration: 6 Feb 2011 → 11 Feb 2011
|Conference||13th International Conference on Computer Aided Systems Theory EUROCAST 2011|
|Period||06.02.2011 → 11.02.2011|