کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388196 | 660920 | 2009 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
In this paper, we investigate the performance of several systems based on ensemble of classifiers for bankruptcy prediction and credit scoring.The obtained results are very encouraging, our results improved the performance obtained using the stand-alone classifiers. We show that the method “Random Subspace” outperforms the other ensemble methods tested in this paper. Moreover, the best stand-alone method is the multi-layer perceptron neural net, while the best method tested in this work is the Random Subspace of Levenberg–Marquardt neural net.In this work, three financial datasets are chosen for the experiments: Australian credit, German credit, and Japanese credit.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 2, Part 2, March 2009, Pages 3028–3033
Journal: Expert Systems with Applications - Volume 36, Issue 2, Part 2, March 2009, Pages 3028–3033
نویسندگان
Loris Nanni, Alessandra Lumini,