An Efficient Expert System For Diabetes By Naïve Bayesian Classifier

A.Ambica; Satyanarayana Gandi; Amarendra Kothalanka

doi:https://doi.org/10.14445/22315381/IJETT-V4I10P165

Research Article | Open Access | Download PDF

Volume 4 | Issue 10 | Year 2013 | Article Id. IJETT-V4I10P165 | DOI : https://doi.org/10.14445/22315381/IJETT-V4I10P165

An Efficient Expert System For Diabetes By Naïve Bayesian Classifier

A.Ambica , Satyanarayana Gandi , Amarendra Kothalanka

Citation :

A.Ambica , Satyanarayana Gandi , Amarendra Kothalanka, "An Efficient Expert System For Diabetes By Naïve Bayesian Classifier," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 10, pp. 4634-4639, 2013. Crossref, https://doi.org/10.14445/22315381/IJETT-V4I10P165

Abstract

In this paper we are proposing an efficient decision support system for Diabetes Disease, apart from the traditional simple support vector machine. We are proposing an efficient two level approach for classifying data. In initial phase we extract optimal feature set from the training data by analyzing the optimality in the dataset, then new dataset is formed as optimal training dataset, now we apply our classification mechanism on the optimal feature set.

Keywords

BGL, Disease, probability, fuzzy

References

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