Sınıflandırıcıların Kalp Hastalığı Verileri Üzerine Performans Karşılaştırması

Bu çalışmada kalp hastalığı verileri kullanılarak bazı sınıflandırıcıların avantajları, dezavantajları göz önünde bulundurularak performans karşılastırmaları yapılmıştır. Araştırmada kullanılan algoritmalar şunlardır: Destek Vektör Makinesi (DVM), Naïve Bayes, J48, Random Forest, Adaboost, Logistic Regresyon, Tek Katmanlı Perceptron, Çok Katmanlı Perceptron, Bagging karar Ağaçları. Burada sonuçların karşılaştırılması için veri setindeki kayıt sayısı, doğruluk ortalaması,  doğru olarak sınıflandırılmış örnekler, yanlış olarak sınıflandırılmış örnekler, kappa istatistiği, ortalama mutlak hata, ortalama kare hata, kök ortalama kare hata, göreceli mutlak hata, kök nispi kare hata gibi ölçütleri kullanıldı. Elde edilen sonuçlara göre en yüksek başarım DVM algoritması sonucunda bulunmuştur.

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Fırat Üniversitesi Mühendislik Bilimleri Dergisi-Cover
  • ISSN: 1308-9072
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 1987
  • Yayıncı: FIRAT ÜNİVERSİTESİ