Ekiz, SimgeErdoğmuş, Pakize2020-04-302020-04-302017978-1-5386-0440-3https://hdl.handle.net/20.500.12684/3132Scientific Meeting on Electric Electronics, Computer Science, Biomedical Engineerings (EBBT) -- APR 20-21, 2017 -- Istanbul Arel Univ, Istanbul, TURKEYWOS: 000413686600009The 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.eninfo:eu-repo/semantics/closedAccessheart diseaseUCI Machine LearningClassificationSupport Vector MachinesEnsemble LearningDecision TreeComparative Study of Heart Disease ClassificationConference ObjectN/A