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

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Published: Dec 31, 2017
Keywords:
Data mining Techniques, Data mining Tools, Diabetic disease, Performance Accuracy

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Sarangam Kodati
Dr. R P. Singh

Abstract

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.

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How to Cite
[1]
Sarangam Kodati and Dr. R P. Singh, “Comparative Performance Analysis of Different Data Mining Techniques and Tools Using in Diabetic Disease”, Int. J. Comput. Eng. Res. Trends, vol. 4, no. 12, pp. 556–561, Dec. 2017.
Issue
Vol. 4 No. 12 (2017): December (2017) Issue
Section
Research Articles
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