Şirket İflaslarının Tahmin Edilmesinde Karar Ağacı Algoritmalarının Karşılaştırmalı Başarım Analizi

-- Bu çalışmada, önemli bir ekonomik problem olan, şirket iflaslarının tahmin edilmesi ele alınmıştır. Bunun için iki yüz kırk farklı şirkete ilişkin finansal özellikleri içeren bir veri seti kullanılmıştır. Ele alınan veri seti, sınıflandırma ve tahmin etmede kullanılan önemli yöntemlerden biri olan karar ağacı yöntemine ilişkin yedi farklı algoritma 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 tahmin edilmesi için uygun bir yöntem olduğu ve kısmen başarılı doğru sınıflandırma yüzdesi elde ettiği gözlemlenmiştir

Comparative Performance Analysis of Decision Tree Algorithms in the Corporate Bankruptcy Prediction

-- 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

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