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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

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Comparative Performance Analysis of Different Data Mining Techniques and Tools Using in Diabetic Disease

Sarangam Kodati, Dr. R P. Singh, , ,
Department of Computer Science and Engineering, Sri Satya Sai University of Technology and Medical Science, Sehore, Bhopal, Madhya Pradesh, India
:10.22362/ijcert/2017/v4/i12/xxxx [UNDER PROCESS]

Data mining means to the process of collecting, searching through, and analyzing a significant amount of data in a database. The most essential and popular data mining methods are classification, association, clustering, prediction or sequential patterns. In health concern businesses, data mining plays a vital role in the early prediction of diseases toughness. This paper explores the early prediction diabetic diabetes using various data mining methods and data mining tools. The dataset has taken 768 instances from PIMA Indian Dataset by determining the accuracy of the data mining techniques in prediction. The analysis proves that Modified J48 Classifier provides the highest comparative durability accuracy than other techniques.

Sarangam Kodati,Dr. R P. Singh(2017). Comparative Performance Analysis of Different Data Mining Techniques and Tools Using in Diabetic Disease. International Journal of Computer Engineering In Research Trends, 4(12), 556-561. Retrieved from

Keywords : Data mining Techniques, Data mining Tools, Diabetic disease, Performance Accuracy

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