Recommendation of Attributes for Heart Disease Prediction using Correlation Measure
S. Chellammal1, R. Sharmila2
1S. Chellammal, Bharathidasan University Constituent Arts and Science College, Navalurkuttapattu, Tiruchirappalli (Tamil Nadu), India.
2R. Sharmila, Bharathidasan University Constituent Arts and Science College, Navalurkuttapattu, Tiruchirappalli (Tamil Nadu), India.
Manuscript received on 21 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 870-875 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11630782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1163.0782S319
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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: Heart diseases are the major cause for human mortality rate. Correct diagnosis and treatment at an early stage will save people from heart disease and will decrease mortality rate due to heart problem. Since ten years various data mining techniques have been used to facilitate the prediction of heart diseases .In general prediction algorithms for trained with huge, known dataset to arrive at a classifier which then predicts the diseases for unknown data with the help of classifying attributes. These attributes also called as features. In this work relevant features are determined for heart disease prediction with known dataset using correlation measures. The results are presented.
Keywords: Correlation Method, Relevant Features, Prediction.
Scope of the Article: Regression and Prediction