Open AccessHeart Disease Prediction System Using K- Nearest Neighbour Classification Technique
Author(s) -
Sowbarnica V. S,
Vismaya,
M Vidhyapoonthalir,
S. Bhuvana
Publication year - 2019
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit195247
Subject(s) - normalization (sociology) , support vector machine , database normalization , computer science , heart disease , nearest neighbour , artificial intelligence , pattern recognition (psychology) , data mining , scalar (mathematics) , feature extraction , k nearest neighbors algorithm , machine learning , mathematics , medicine , cardiology , geometry , sociology , anthropology
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%.