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A Wavelet based Feature Selection Method to Improve Classification of Large Signal-type Data  

Jang, Woosung (Department of Industrial Engineering, Seoul National University)
Chang, Woojin (Department of Industrial Engineering, Seoul National University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.32, no.2, 2006 , pp. 133-140 More about this Journal
Abstract
Large signal type data sets are difficult to classify, especially if the data sets are non-stationary. In this paper, large signal type and non-stationary data sets are wavelet transformed so that distinct features of the data are extracted in wavelet domain rather than time domain. For the classification of the data, a few wavelet coefficients representing class properties are employed for statistical classification methods : Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Network etc. The application of our wavelet-based feature selection method to a mass spectrometry data set for ovarian cancer diagnosis resulted in 100% classification accuracy.
Keywords
classification; wavelet transform; feature extraction;
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