International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

A Comparative Study on Decision Tree and Random Tree Approach in Predicting Heart Diseases

Author : Sudhanva S ¹ Tarun T N ² Sujay C V ³ Vishal D A ⁴ Yuvraaj ⁵ Spandana S G ⁶

Date of Publication :21st July 2022

Abstract: Heart disease is one of the leading causes of death in the globe. All doctors cannot be equally proficient in every domain and well versed and skillfull doctors canâ€™t be available at all time. An automated medical diagnosis system would improve medical treatment while simultaneously lowering expenses. Predicting the course of illness is a difficult endeavor. Data mining is used to infer diagnostic principles automatically and assist professionals in making the diagnosis process more trustworthy. Researchers employ a variety of data mining approaches to assist health care practitioners in predicting cardiac disease. A classification model would be a fit model for predicting diseases accurately. We present you with a comparison of two classification models, Decision trees and Random Forest Models. We find that Random Forest method performs better than Decision Tree model

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