Research on the Machine Learning Algorithms on Heart Condition Predictions
Geetha M1, Ganesan R2, Tallam Tharun Sai3
1Geetha M, School of Computer Science and Engineering, Vellore Institute of Technology, Campus, Chennai (Tamil Nadu), India.
2Ganesan R, School of Computer Science and Engineering, Vellore Institute of Technology, Campus, Chennai (Tamil Nadu), India.
3Tallam Tharun Sai, School of Computer Science and Engineering, Vellore Institute of Technology, Campus, Chennai (Tamil Nadu), India.
Manuscript received on 13 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript Published on 26 July 2019 | PP: 1377-1384 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F12790486S419/19©BEIESP | DOI: 10.35940/ijitee.F1279.0486S419
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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: Now-a-days Health care monitoring widely uses Internet of Things (IoT) and big data which is further integrated into wearable bio sensors. This paper is about finding the best algorithm for predicting the heart condition using different machine learning algorithms. In this we have also included the basic Artificial Neural Networks algorithm for predicting the heart condition of an individual. In this work we had predicted the persons heat conditions by knowing some key attributes. By increasing the use of machine learning algorithms, the accuracy of each algorithm is calculated and the quality and value of the health services increases efficiency. This is mainly about how different the algorithms predict and the accuracy of each algorithm. Here the ANN has the height accuracy when compared to all other machine learning algorithms like, SVM-ploy, SVM-RBF, Naïve Bayes, Decision tree, Random Forest, K-Nearest Neighbor.
Keywords: Decision Tree, K- Nearest Neighbour, Naive Bayes, Random forest, SVM Poly, SVM RBF, ANN (Artificial Neural Networks Using Multi-Layer Perceptron).
Scope of the Article: Computer Science and Its Applications