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

Sarangam Kodati, Dr. R P. Singh, , ,
Affiliations
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]


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.


Citation
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 http://ijcert.org/ems/ijcert_papers/V4I1204.pdf


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

References
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mining approach which balances Fitting and Generalization Springer 2008. 


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Citation Index


Citations Indices All
Citations 1026
h-index 14
i10-index 20
Source: Google Scholar

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Acceptance Rate (By Year)
Year Rate
2021 10.8%
2020 13.6%
2019 15.9%
2018 14.5%
2017 16.6%
2016 15.8%
2015 18.2%
2014 20.6%

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DOI:10.22362/ijcert