Int. J. Biomedical Engineering and Technology, Vol. 4, No. 2, 2010
A maximum margin classifier for non-linearly separable pattern classes, using a feature space sampling technique, applied to chromosome classification S. Ganesh Vaidyanathan* Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur 602105 (TN), India E-mail:
[email protected] *Corresponding author
Bibhas Kar Department of Medical Genetics, Apollo Hospitals, Greams Lane, Chennai 600006 (TN), India E-mail:
[email protected]
N. Kumaravel Department of Electronics and Communication Engineering, Anna University, Guindy, Chennai 600025 (TN), India E-mail:
[email protected] Abstract: The classification of chromosomes using a classifier is generally inaccurate owing to closeness of features belonging to various chromosomes which poses a linearly inseparable problem. This paper proposes a novel technique to obtain the non-linear decision boundary. An average classification accuracy of 93% was achieved with this technique which involves arriving at the non-linear decision boundary by joining and smoothening the sample points obtained by sampling the feature space within a boundary limited by the range of the data and by the curves of the best fit to the two classes. The technique works for feature space of any dimension. Keywords: feature space; curve fitting; sampling; optimal boundary points; non-linear boundary; binary pattern classifier. Reference to this paper should be made as follows: Ganesh Vaidyanathan, S., Kar, B. and Kumaravel, N. (2010) ‘A maximum margin classifier for non-linearly separable pattern classes, using a feature space sampling technique, applied to chromosome classification’, Int. J. Biomedical Engineering and Technology, Vol. 4, No. 2, pp.123–133. Biographical notes: S. Ganesh Vaidyanathan obtained his MS in Electronics and Control from BITS, Pilani, and ME in Mechatronics from Madras institute of Technology. He is currently working as an Assistant Professor in the Copyright © 2010 Inderscience Enterprises Ltd.
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