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Advanced Multistage Feature-based Classification Model  

Kim, Jae-Young (Dept. of Information Eng., Myong Ji University)
Park, Dong-Chul (Dept. of Electronics Eng., Myong Ji University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.47, no.3, 2010 , pp. 36-41 More about this Journal
Abstract
An advanced form of Multistage Feature-based Classification Model(AMFCM), called AMFCM, is proposed in this paper. AMFCM like MFCM does not use the concatenated form of available feature vectors extracted from original data to classify each data, but uses only groups related to each feature vector to classify separately. The prpposed AMFCM improves the contribution rate used in MFCM and proposes a confusion table for each local classifier using a specific feature vector group. The confusion table for each local classifier contains accuracy information of each local classifier on each class of data. The proposed AMFCM is applied to the problem of music genre classification on a set of music data. The results demonstrate that the proposed AMFCM outperforms MFCM by 8% - 15% on average in terms of classification accuracy depending on the grouping algorithms used for local classifiers and the number of clusters.
Keywords
Multistage feature; Classification model; Pattern classification; Music genre classification;
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Times Cited By KSCI : 3  (Citation Analysis)
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