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Examining Classification Techniques in Data Mining for PIMA Indian Diabetes Dataset


S. Janani , BHARATHIAR UNIVERSITY; Dr. D. RamyaChitra, Bharathiar University


Data Mining, Classification, PIMA Indian Diabetes Dataset


Classification techniques have been widely used in the medical field for accurate classification than an individual classifier. This paper presents computational intelligence techniques for Diabetes Patient Classification. This paper evaluates the selected 5 classification algorithms (Naïve Bayes, Multilayer Perception, Decision Table, J48 and FT) for the classification of diabetes patient datasets. The aim of this paper is to investigate the performance of different classification techniques. In this paper we are analyzing the performance of 5 classification algorithms. We use the PIMA Indian diabetes datasets for calculating the performance of classification algorithms by using the training set parameter. And finally a comparative analysis based on the performance factors such as the Classification Accuracy, Error Rate and execution time is performed on all the algorithms.

Other Details

Paper ID: IJSRDV4I90408
Published in: Volume : 4, Issue : 9
Publication Date: 01/12/2016
Page(s): 629-633

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