International Journal of Pharma and Bio Sciences
ijpbs.net
editorijpbs@rediffmail.com (or) editorofijpbs@yahoo.com (or) prasmol@rediffmail.com
10.22376/ijpbs.2019.10.1.p1-12
Volume 8 Issue 3
2017 (July - September)
A predictive model for heart disease using clustering techniques
Data mining is the area of computer and information science with large perspective of knowledge discovery from large database. Now a days people are dependent on furious timetable and garbage sustenance which impact the heart basically. Prediction of Heart diseasae utilizing different clustering algorithms are implemented in this paper. Grouping of data into related groups is known as clustering.In this work we have implemented K-Means, Hierarchical method and DBSCAN.And compared the results which are genereated by the above algorithms and declaring which is the best algorithm for the prediction of the heart disease.
A.SOWMITH, V.SUCHARITA, P.SOWJANYA AND B.GEETHA KRISHNA
Clustering, Heart Disease, Data Mining,
K Means, Hierarchical, DBSCAN.
529-534