INTERNATIONAL RESEARCH JOURNAL OF SCIENCE ENGINEERING AND TECHNOLOGY

( Online- ISSN 2454 -3195 ) New DOI : 10.32804/RJSET

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A REVIEW ON HEART DISEASE PREDICTION USING HYBRID CLASSIFIER

    2 Author(s):  MUDASSIR AHMAD,DR. SONIA VATTA

Vol -  9, Issue- 2 ,         Page(s) : 18 - 24  (2019 ) DOI : https://doi.org/10.32804/RJSET

Abstract

Heart diseases are one of the major causes of death nowadays. Smoking, consumption of alcohol in large quantity, cholesterol, and pulse rate are the reason of heart diseases. This research work, is based on heart disease prediction using data mining. The prediction analysis is the technique of data mining which can predict further possibilities based in the current information. The data set has 13 numbers of attributes for the heart disease prediction. In the previous research work, the SVM classifier is applied for the heart disease prediction. Due to large number of attributes in the dataset, SVM classifier is not able to classify all the attributes due to which accuracy is low. In this work, the hybrid classifier will be designed based on the random forest and decision tree classifier. The random forest classifier will extract features of the dataset and decision tree classifier will generate the final predicted results. The proposed and existing techniques will be implemented analyzed in terms of accuracy, precision, recall and execution time.

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