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Feature Ranking for Detection of Neuro-degeneration and Vascular Dementia in micro-Raman spectra of Platelet  

Park, Aa-Ron (The School of Electronic and Computer Engineering, Chonnam National University)
Baek, Sung-June (The School of Electronic and Computer Engineering, Chonnam National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.48, no.4, 2011 , pp. 21-26 More about this Journal
Abstract
Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.
Keywords
feature ranking; feature selection; pattern recognition; Raman spectroscopy;
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