Yazar "Öztürk, Gürkan" için Endüstri Mühendisliği Bölümü listeleme
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Arrhythmia Classification via k-Means based Polyhedral Conic Functions Algorithm
Çimen, Emre; Öztürk, Gürkan (IEEE, 2016)Heart disease is one of the important cause of death. In this study, we used ECG data obtained from MIT-BIH database to classify arrhythmias. We select 5 classes; normal beat (N), right bundle branch block (RBBB), left ... -
Clustering Based Polyhedral Conic Functions Algorithm in Classification
Öztürk, Gürkan; Çiftçi, Mehmet Tahir (Amer Inst Mathematical Sciences-Aims, 2015)In this study, a new algorithm based on polyhedral conic functions (PCFs) is developed to solve multi-class supervised data classification problems. The k PCFs are constructed for each class in order to separate it from ... -
A Hybrid Genetic Algorithm For the Quadratic Assignment Problem on Graphics Processing Units
Özçetin, Erdener; Öztürk, Gürkan (2016)Bu çalışmada karesel atama probleminin çözümü için melez bir genetik algoritma önerilmiştir. Önerilen algoritmanın en zaman alıcı bölümleri amaç fonksiyonun hesaplanması ve yerel arama operatörüdür. Bu nedenle algoritmanın ... -
An incremental piecewise linear classifier based on polyhedral conic separation
Öztürk, Gürkan; Bagirov, Adil M.; Kasımbeyli, Refail (Springer, 2015)In this paper, a piecewise linear classifier based on polyhedral conic separation is developed. This classifier builds nonlinear boundaries between classes using polyhedral conic functions. Since the number of polyhedral ... -
Max Margin Polyhedral Conic Function Classifier
Öztürk, Gürkan; Ceylan, Gurhan (IEEE, 2016)In classification problems, generalization ability has a key role for successful prediction. Well known Support Vector Machine classifier, tries to increase generalization ability via maximizing the margin, which is the ... -
A novel piecewise linear classifier based on polyhedral conic and max-min separabilities
Bagirov, Adil M.; Ugon, Julien; Webb, Dean; Öztürk, Gürkan; Kasımbeyli, Refail (Springer, 2013)In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is developed. This algorithm consists of two main stages. In the first stage, a polyhedral conic set is used to identify data ...