Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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A Wavelet based Feature Selection Method to Improve Classification of Large Signal-type Data

웨이블릿에 기반한 시그널 형태를 지닌 대형 자료의 feature 추출 방법

  • Jang, Woosung (Department of Industrial Engineering, Seoul National University) ;
  • Chang, Woojin (Department of Industrial Engineering, Seoul National University)
  • Published : 2006.06.30
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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

References

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