Research Article
Analyzing the Comparison of C4.5, CART and C5.0 Algorithms on Heart Disease Dataset using Decision Tree Method
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303221, author={Khin Lay Myint and Hlaing Htake Khaung Tin}, title={Analyzing the Comparison of C4.5, CART and C5.0 Algorithms on Heart Disease Dataset using Decision Tree Method}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={data mining classification algorithms decision tree patient data-base c45 cart c50}, doi={10.4108/eai.27-2-2020.2303221} }- Khin Lay Myint
Hlaing Htake Khaung Tin
Year: 2021
Analyzing the Comparison of C4.5, CART and C5.0 Algorithms on Heart Disease Dataset using Decision Tree Method
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303221
Abstract
Data acquisition methods can be expected for patients suffering from heart disease. The resolution of this learning was to compare a similar data mining algorithm to the calculation of heart disease. This research paper proposed the traditional decision tree procedure and weighted decision tree procedure. Traditional decision tree process consists of C4.5, C5.0, CART processes. The weighted decision process is established suitable weights of training cases based on naïve Bayesian theorem before trying to construct a decision tree model. The main objectives of this research paper are (1) to know the opera-tion of C4.5 process, Cart and C5.0 process, (2) to learn how to analysis the traditional decision tree and weighted decision tree algorithms are compared results from both training and testing dataset for heart disease