Volume : III, Issue : VI, June - 2013

Pattern Recognition for Diabetic Spectral Data Using Machine Learning Approaches

Dharuman C, Venkatesan P

Abstract :

A vector representation of spectra leads to high dimensional problems. Hence the Machine Learning approaches are required for the analysis of the high dimensional diabetic Spectral data. The Multilayer perception (MLP) Radial Basis Function Network Support Vector Machine and Logistic Regression Model were applied to the diabetic spectra data. The efficiency of the models are evaluated by sensitivity, specificity and accuracy. The results show that the Neural Network Models perform better than Logistic Regression and Support Vector Machine out performs the ANN Models.

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Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Dharuman C, Venkatesan P Pattern Recognition for Diabetic Spectral Data Using Machine Learning Approaches Indian Journal of Applied Research, Vol.III, Issue.VI June 2013

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