Prediction of Heart Diseases in Comparison with Different Machine Learning Algorithms
K. Jayakiran1, M. Pranavi2, M. Novika3, V. Tejaswini4, N. Rajesh5
1K.Jayakiran, Department of Computer Science Engineering, KLEF, Vaddeswaram (Andhra Pradesh), India.
2M.Pranavi, Department of Computer Science Engineering, KLEF, Vaddeswaram (Andhra Pradesh), India.
3M.Novika, Department of Computer Science Engineering, KLEF ,Vaddeswaram (Andhra Pradesh), India.
4V.Tejaswini, Department of Computer Science Engineering, KLEF ,Vaddeswaram (Andhra Pradesh), India.
5N.Rajesh, Associate Professor, Department of Computer Science Engineering, KLEF, Vaddeswaram (Andhra Pradesh), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 328-332 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3581048619/19©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: Machine Learning is one of the field of computer technological know-how has the potential to expertise to “examine” and additionally get admission to the statistics. Predication of heart disease based on gadget studying set of rules for the actual time data is constantly an enthusiastic case. The coronary heart illnesses prediction utility is an give up person support and on line session task The task can be performed through the usage of device different algorithms to locate the accuracy of the dataset which incorporate the attributes like BP, sugar ,heartbeat and many other. The dataset may be carried out in R language to discover the accuracy based at the algorithm. Here, In this dataset we have were given 14 attributes with three hundred instances has been used as the primary dataset for the training and testing out of the developed gadget. There are distinct classifiers, specifically Decision Tree (DT), Naive Bayes (NB), Random Forest(RF), K –Nearest Neighbour (KNN) , and Neural Network(NN) been used to evaluate the accuracy of the algorithm.
Keyword: Decision Tree, Naive Bayes, Neural Network.
Scope of the Article: Machine Learning