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http://dx.doi.org/10.22937/IJCSNS.2022.22.5.20

Comparing Results of Classification Techniques Regarding Heart Disease Diagnosing  

AL badr, Benan Abdullah (College of Science, Department of Computer Science and information, Majmaah University)
AL ghezzi, Raghad Suliman (College of Science, Department of Computer Science and information, Majmaah University)
AL moqhem, ALjohara Suliman (College of Science, Department of Computer Science and information, Majmaah University)
Eljack, Sarah (College of Science, Department of Computer Science and information, Majmaah University)
Publication Information
International Journal of Computer Science & Network Security / v.22, no.5, 2022 , pp. 135-142 More about this Journal
Abstract
Despite global medical advancements, many patients are misdiagnosed, and more people are dying as a result. We must now develop techniques that provide the most accurate diagnosis of heart disease based on recorded data. To help immediate and accurate diagnose of heart disease, several data mining methods are accustomed to anticipating the disease. A large amount of clinical information offered data mining strategies to uncover the hidden pattern. This paper presents, comparison between different classification techniques, we applied on the same dataset to see what is the best. In the end, we found that the Random Forest algorithm had the best results.
Keywords
Google Colab; classification technique; Random Forest; Python language; machine learning;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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