Heart Disease Prediction Using Effective Machine Learning Techniques
Avinash Golande1, Pavan Kumar T2

1Avinash Golande, Research Scholar, K L University, Vijayawada, (Andhra Pradesh), India.
2Dr. Pavan Kumar T, Professor, K L University, Vijayawada, (Andhra Pradesh), India.
Manuscript received on 07 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 944-950 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A11740681S419/2019©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: In today’s era deaths due to heart disease has become a major issue approximately one person dies per minute due to heart disease. This is considering both male and female category and this ratio may vary according to the region also this ratio is considered for the people of age group 25-69. This does not indicate that the people with other age group will not be affected by heart diseases. This problem may start in early age group also and predict the cause and disease is a major challenge nowadays. Here in this paper, we have discussed various algorithms and tools used for prediction of heart diseases.
Keywords: Classification, Heart Disease, Decision Tree, Data Mining.
Scope of the Article: Machine Learning