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2006
Springer

Evolutionary Tuning of Combined Multiple Models

11 years 11 months ago
Evolutionary Tuning of Combined Multiple Models
Abstract. In data mining, hybrid intelligent systems present a synergistic combination of multiple approaches to develop the next generation of intelligent systems. Our paper presents an integration of a Combined Multiple Models (CMM) technique with an evolutionary approach that is used for tuning of parameters. Proposed hybrid classifier was tested in microarray analysis domain. This domain was chosen intentionally, because of the nature of Combined Multiple Models classifiers that are specialized in solving problems with high dimensionality and contain low number of samples. Evolutionary tuning of parameters in combination with validation dataset enables fine tuning of parameters that are usually set to pre-defined values. Using this technique we made another step in leveling the accuracy of comprehensible classifiers to those represented by ensembles of classifiers.
Gregor Stiglic, Peter Kokol
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where KES
Authors Gregor Stiglic, Peter Kokol
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