Genetic Algorithm과 다중부스팅 Classifier를 이용한 암진단 시스템

It is believed that the anomalies or diseases of human organs arc identified by the analysis of the patterns. This paper proposes a new classification technique for the identification of cancer discasc using the proteome patterns obtaincd from two-dimensional polyaclylamide gel electrophoresis(2-D PAGE). In thc new classification method, three different classification methods such as support vector machinc(SVM), multi-layer perceptron(MLP) and k-nearest neighbor(k-NN) are extended by multi-boosting method in an array of subclassificrs and thc results of each subclassifier are merged by ensemble method. Gcnctic algorithm was applied to obtain optimal feature set in each subclassifier. We applied our method to empirical data set from cancer research and the method showcd thc better accuracy and more stablc performance than single classifier.