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July 2016 Issue Vol.6 No.7
A Novel Technique for Prediction of Diabetic Patients Data Using Naives Bayes Classification in WEKA Tool
https://archive.org/download//vol6no0701/vol6no0701.pdf
S.Nivetha
Assistant Professor, Department of Computer Science, Kamban Arts and Science College,Pollachi,Tamil Nadu, India
Dr.A.Geetha
Assistant Professor, PG & Research Department of Computer Science,Chikkanna Govt. Arts College, Tirupur, Tamil Nadu, India
Abstract:
Data mining is a process of extracting information from a dataset and transform it into understandable structure for further use, also it discovers patterns in large data sets. Data mining has number of techniques such as pre-processing, classification. Classification is a technique used for predicting group for the diabetic dataset instance. In this paper, classification on diabetes database are developed classifiers are compared with the result based on certain parameters using WEKA tool. India is suffering from diabetes patients of the population with equal rates in both women and men resulted in deaths with worldwide. A comparative analysis has been performed with the classifiers which result in the chance of diabetic patients getting heart disease. The performances compared with precision, recall, F-measure, Kappa statistic, root mean square and time seconds build the model has exhibited a great overall performance.
Keywords:Data Mining,Diabetic Data,RF,NB,WEKA.
