Ensemble Classification Model for Diabetes Prediction in Data Mining
Munendra Kumar1, Anuj Kumar2
1Munendra Kumar, Research Scholar, IEC College of Engineering & Technology, Greater Noida(U.P.), India.
2Anuj Kumar, Associate Professor, IEC College of Engineering & Technology, Greater Noida(U.P.), India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1240-1243 | Volume-8 Issue-4, November 2019. | Retrieval Number: C5285098319/2019©BEIESP | DOI: 10.35940/ijrte.C5285.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The prediction analysis is the approach which can predict the future possibilities based on the current information. The diabetes prediction is the approach which is applied to predict the diabetes based on the various attributes. The diabetes dataset has various attributes and based on that attributes diabetes can be predicted. In the previous years approach of SVM is applied for the diabetes prediction. To improve accuracy of diabetes prediction voting based classification is applied in this paper. The proposed model is implemented in python and results are analyzed in terms of accuracy, execution time.
Keywords: Diabetes, SVM, Voting.
Scope of the Article: Classification.