COMBINATION OF KNN CLASSIFIERS BASED ON MULTIPLE CORRESPONDENCE ANALYSIS

This paper presents a KNN classifier combination method based on multiple correspondence analysis (MCA-KNN). This combination method is applied to written character recognition. Four kinds of features are extracted from same sample set and four result sets are obtained from these feature sets through KNN classifier. Through MCA-KNN, the four result sets are combined to get the final result. The experimental results in this paper demonstrate MCA-KNN's capability to reduce classifying error rate.