Prediction of Diabetics using Factor Analysis
S. Kavitha1, E. Srividhya2, S. Muthuselvan3
1S. Kavitha, Department of Computer Science and Technology, SRM Institute of Science and Technology, Chennai, (Tamil Nadu), India.
2E. Srividhya, Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Chennai, (Tamil Nadu), India.
3S. Muthuselvan, Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Chennai, (Tamil Nadu), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1517-1521 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2594037619/19©BEIESP
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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: A diabetic is a fast growing disease in the world so prediction of diabetics is so important for quick decision making. The data mining techniques are used for analysis of medical database. The one of the data mining technique is statistical methods which is playing a major role for analysis and prediction of diabetics in accurate manner. The factor analysis is a method of reducing huge variables into lesser number of factors. It extracts the maximum common variances from all the variables and puts into the common variables. These common variables are used for further analysis. The factor analysis of dataset will give an effective outcome or better result to predict and also diagnose the diabetes disease. This paper focused on increasing the quality and accuracy of knowledge for diabetes disease treatment.
Keywords: Data Mining, Factor Analysis, Diabetic, prediction.
Scope of the Article: Data Mining.