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Öz

— In this study, corporate bankruptcy prediction, a crucial economic problem is tackled. To do this, a data set of 240 distinct companies with financial features is used. This data set is applied to one of the most important classification and forecasting methods, i.e. decision tree method. Seven different decision tree algorithms are evaluated in terms of accuracy percentage, mean absolute error, root mean squared error, precision, recall, F-measure. According to experimental results, decision tree algorithms are appropriate methods for corporate bankruptcy prediction with relatively successful accuracy rates

Anahtar Kelimeler

• — forecasting, decision tree algorithms, classification, corporate bankruptcy

Şirket İflaslarının Tahminlenmesinde Karar Ağacı Algoritmalarının Karşılaştırmalı Başarım Analizi

Öz

Bu çalışmada, önemli bir ekonomik problem olan, şirket iflaslarının tahminlenmesi ele alınmıştır. Bunun için iki yüz kırk farklı şirkete ilişkin finansal özellikleri içeren bir veri seti kullanılmıştır. Değinilen veri seti, sınıflandırma ve tahminlemede kullanılan önemli yöntemlerden biri olan karar ağacı yöntemine ilişkin yedi farklı algoritma ile uygulanarak, doğru sınıflandırma yüzdesi, ortalama mutlak hata, ortalama karesel hatanın karekökü, kesinlik, geri çağırma, F-ölçütü gibi ölçütler bakımından değerlendirilmiştir. Deneysel sonuçlar incelendiğinde, karar ağacı algoritmalarının şirket iflaslarının tahminlenmesi için uygun bir yöntem olduğu ve kısmen başarılı doğru sınıflandırma yüzdesi elde ettiği gözlemlenmiştir.

Anahtar Kelimeler

• tahminleme, karar ağacı algoritmaları, sınıflandırma, şirket iflasları

Kaynakça

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