Bukti Review Jurnal : K-Fold Cross Validation for Selection of Cardiovascular Disease Diagnosis Features by Applying Rule-Based Datamining

Normawati, Dwi and Juwitaningtyas, Titisari and JONES, ANNA HENDRI SOLELIZA (2019) Bukti Review Jurnal : K-Fold Cross Validation for Selection of Cardiovascular Disease Diagnosis Features by Applying Rule-Based Datamining. https://simple.ascee.org/, 1 (2). p. 2019. ISSN 2158-107X (print), 2156-5570 (online)

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Abstract

Coronary heart disease occurs when atheroclerosis inhibits blood flow to the heart muscle in the coronary arteries. This disease is often the cause of human death. The method for diagnosing coronary heart disease that is often a doctor's referral is coronary angiography, but it is invasive, expensive, and high-risk. This study aims to analyze the effect of k-Fold Cross-Validation (CV) on the dataset to create features based on the rules used to diagnose coronary heart disease. This study uses the Cleveland heart disease dataset, where feature selection is performed using a medical expert-based method (MFS) and a computer-based method, Variable Precision Rough Set (VPRS). Evaluation of the classification performance using the k-fold 10-fold, 5-fold and 3-fold methods. The results showed the number of different attribute selection results in each fold, both for the VPRS and MFS methods, with the highest accuracy score in the VPRS method 76.34% with k = 5, while the MTF accuracy was 71.281% with k = 3.

Item Type:	Artikel Umum
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisi / Prodi:	Faculty of Applied Science and Technology (Fakultas Sains Dan Teknologi Terapan) > S1-Information System (S1-Sistem Informasi)
Depositing User:	S.T.,M.Eng Dwi Normawati
Date Deposited:	30 Nov 2021 05:18
Last Modified:	30 Nov 2021 05:18
URI:	http://eprints.uad.ac.id/id/eprint/29762

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