An Improved Feature Selection using Maximized Signal to Noise Ratio Technique for TC

Authors:
K. Lakshmi;Dr. Saswati Mukherjee
Affiliations:
Anna University, India;Anna University, India
Venue:
ITNG '06 Proceedings of the Third International Conference on Information Technology: New Generations
Year:
2006

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Abstract

Aim of this work is to produce excellent accuracy with reduced feature set by a simple method. When the profile built using a feature selection method called MSNR (Maximized Signal to Noise Ratio) combined with modified fractional similarity method, it performs in a competitive manner. MSNR identifies the highly contributing features and increases the distance between the profiles. Experimental results show that when we select only top 3% features of each class using MSNR (Maximized Signal To Noise Ratio) and use these profiles in combination with modified fractional method, achieved 90% classification accuracy.