Author(s)

Jing Chen

Corresponding Author

Jing Chen

Abstract

Based on the above characteristic, firstly genetic algorithms, which have been widely used in optimization problems, was applied to feature selection techniques, and then a multiple classifier system model was designed as extension of genetic-algorithm-based feature selection techniques. As there are correlations among features, a new multiple classifier system model was constructed with disjoint feature subspace constraint. These two models were trained by supervised methods and oriented by improving the classification accuracy. The construction of multiple classifier system is completed by genetic algorithms, which determines what optimized feature subspace each sub-classifier should uses.

Keywords

Genetic Algorithms, Object-Oriented, Feature Selection, Multiple Classifier System.