کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10323143 | 660903 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Predicting multilateral trade credit risks: comparisons of Logit and Fuzzy Logic models using ROC curve analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Predicting multilateral trade credit risks: comparisons of Logit and Fuzzy Logic models using ROC curve analysis Predicting multilateral trade credit risks: comparisons of Logit and Fuzzy Logic models using ROC curve analysis](/preview/png/10323143.png)
چکیده انگلیسی
The results show that FL exceeds Logit in terms of overall classification accuracy and prediction accuracy. However, by incorporating measurement in the form of ROC curves, Logit is proven to outperform FL in classifying non-default firms. This suggests that though FL is superior in overall accuracy and in classifying default firms, Logit is preferable in situations where higher accuracy in classifying non-default firms is preferred. The stability of the models is also demonstrated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 28, Issue 3, April 2005, Pages 547-556
Journal: Expert Systems with Applications - Volume 28, Issue 3, April 2005, Pages 547-556
نویسندگان
Tseng-Chung Tang, Li-Chiu Chi,