Heart Disease Prediction Using Hybrid Classifier
Journal: International Journal of Application or Innovation in Engineering & Management (IJAIEM) (Vol.8, No. 8)Publication Date: 2019-09-09
Authors : Mudassir Ahmad Sonia Vatta;
Page : 039-046
Keywords : ;
Abstract
The data mining is the approach which can extract useful information from the data. This research work is related to heart disease prediction. The prediction analysis is the approach which can predict future possibilities based on the current information. The hybrid classifier is designed in this research work, for the heart disease prediction. The hybrid classifier is combination of random forest and decision tree classifier. The random forest classifier extract the information and decision tree generate final classifier result. The proposed hybrid model is implemented in python and results are compared with SVM classifier. It is analyzed that hybrid classifier has maximum performance as compared to SVM classifier Keywords: Hybrid classifier, SVM, Heart disease prediction, Data Mining
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Last modified: 2019-09-09 19:42:57