Heart Disease Prediction System Using K- Nearest Neighbour Classification Technique

Authors(4) :-Sowbarnica V. S, Vismaya V, Vidhyapoonthalir M, Dr. S. Bhuvana

The heart is an operating system of the human body .If it does not function properly it will affect other parts also. Heart disease problem describes a range of conditions that affect your heart. The existing system uses Support Vector Machine (SVM), it propose a system for heart disease prediction. The method will help doctor to explore their data and predict heart disease accurately. The Hospitals do not provide the same quality of service even though they provide the same type of service. The Proposed system includes the following phases: Pre-Processing of the input data with Min-Max scalar and Normalization ,Feature extraction by PSO algorithm, Classification of data by K-Nearest Neighbour. In comparison with the existing approach ,the proposed approach significantly improves the accuracy from 51% to 76.66%.

Authors and Affiliations

Sowbarnica V. S
Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Vismaya V
Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Vidhyapoonthalir M
Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Dr. S. Bhuvana
Associate Professor, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

Heart disease,pre-processing, PSO(Particle Swarm Optimization),KNN(K-Nearest Neighbour).

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 229-236
Manuscript Number : CSEIT195247
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sowbarnica V. S, Vismaya V, Vidhyapoonthalir M, Dr. S. Bhuvana, "Heart Disease Prediction System Using K- Nearest Neighbour Classification Technique", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.229-236, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195247
Journal URL : http://ijsrcseit.com/CSEIT195247

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