Comparative Study of Heart Disease Classification
| dc.contributor.author | Ekiz, Simge | |
| dc.contributor.author | Erdoğmuş, Pakize | |
| dc.date.accessioned | 2020-04-30T22:41:09Z | |
| dc.date.available | 2020-04-30T22:41:09Z | |
| dc.date.issued | 2017 | |
| dc.department | DÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
| dc.description | Scientific Meeting on Electric Electronics, Computer Science, Biomedical Engineerings (EBBT) -- APR 20-21, 2017 -- Istanbul Arel Univ, Istanbul, TURKEY | en_US |
| dc.description | WOS: 000413686600009 | en_US |
| dc.description.abstract | The aim of this paper is to compare two important machine learning platform results for the same dataset. With this aim, we conducted an experiment to classify heart disease both in Matlab(C) environment and WEKA(C), by using six different algorithms. Linear SVM, Quadratic SVM, Cubic SVM, Medium Gaussian SVM, Decision Tree and Ensemble Subspace Discriminant machine learning approaches are used for classifying the heart disease. | en_US |
| dc.description.sponsorship | IEEE Turkey Sect, IEEE EMB, IEEE | en_US |
| dc.identifier.isbn | 978-1-5386-0440-3 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12684/3132 | |
| dc.identifier.wosquality | N/A | en_US |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | 2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (Ebbt) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | heart disease | en_US |
| dc.subject | UCI Machine Learning | en_US |
| dc.subject | Classification | en_US |
| dc.subject | Support Vector Machines | en_US |
| dc.subject | Ensemble Learning | en_US |
| dc.subject | Decision Tree | en_US |
| dc.title | Comparative Study of Heart Disease Classification | en_US |
| dc.type | Conference Object | en_US |
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