Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Knowledge Acquisition form Examples Vis Multiple Models
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
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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.