Feature selection using Haar wavelet power spectrum |
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Authors: | Prabakaran Subramani Rajendra Sahu and Shekhar Verma |
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Institution: | (1) ABV-Indian Institute of Information Technology and Management, Gwalior, India |
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Abstract: | Background Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification
using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets.
The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize
them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this
paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on
expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. |
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