1 |
G. Menardi and N. Torelli, "Training and assessing classification rules with imbalanced data," Data Mining and Knowledge Discovery, Vol.28, No.1 pp.92-122, 2014.
DOI
|
2 |
W. H. Beaver, "Financial ratios as predictors of failure, Journal of Accounting Research," Vol.4, pp.71-111, 1966.
DOI
|
3 |
E. I. Altman, "Financial ratios discriminant analysis and the prediction of corporate bankruptcy," The journal of finance, Vol.23, No.4, pp.589-609, 1968.
DOI
|
4 |
J. A. Ohlson, "Financial ratios and the probabilistic prediction of bankruptcy," Journal of accounting research, Vol.18, No.1, pp.109-131, 1980.
DOI
|
5 |
M. E. Zmijewski, "Methodological issues related to the estimation of financial distress prediction models," Journal of Accounting Research, Vol.22, pp.59-82, 1984.
DOI
|
6 |
R. O. Edmister, "An empirical test of financial ratio analysis for small business failure prediction," Journal of Financial and Quantitative Analysis, Vol.7, No.2, pp.1477-1493, 1972.
DOI
|
7 |
M. D. Odom and R. Sharda, "A neural network model for bankruptcy prediction. In Proceedings of the International Joint Conference on Neural networks," Vol.2, pp.163-168, 1990.
|
8 |
K. Y. Tam and M. Y. Kiang, "Managerial applications of neural networks: the case of bank failure predictions," Management Science, Vol.38, No.7, pp.926-947, 1992.
DOI
|
9 |
N. Lunardon, G. Menardi, and N. Torelli, ROSE: A Package for Binary Imbalanced Learning, r-project.org, 2014.
|
10 |
M. Kubat and S. Matwin, "Addressing the curse of imbalanced training sets: one-sided selection," Proceedings of the Fourteenth International Conference on Machine Learning, pp.179-186, 1997.
|
11 |
B. Efron and R. Tibshirani, An introduction to the bootstrap, Chapman and Hall, 1993.
|
12 |
F. E. J. Tay and L. J. Cao, "Modified support vector machines in financial time series forecasting," Neurocomputing, Vol.48, pp.847-861, 2002.
DOI
|
13 |
이영찬, "인공신경망과 Support Vector Machine의 기업부도예측 성과 비교," 한국지능정보시스템학회 춘계학술대회논문집, pp.211-218, 2004.
|
14 |
C. Serrano-Cinca, "Self-organizing neural networks for financial diagnosis," Decision Support Systems, Vol.17, No.3, pp.227-238, 1996.
DOI
|
15 |
J. Yang and V. Honavar, "Feature subset selection using a genetic algorithm," IEEE Intelligent Systems and their Applications, Vol.13, No.2, pp.44-49, 1998.
DOI
|
16 |
김경재, 한인구, "퍼지 신경망을 이용한 기업부도예측," 지능정보연구, 제7권, 제1호, pp.135-146, 2001.
|
17 |
강필성, 조성준, "데이터 불균형 해결을 위한 Under-Sampling 기반 앙상블 SVMs," 대한산업공학회 춘계공동학술대회 논문집, pp.291-298, 2006.
|
18 |
이재동, 이지형, "데이터 불균형 문제 해결을 위한 K-means Clustering 기반 SVM앙상블 기법," 한국정보과학회 한국컴퓨터종합학술대회 논문집, pp.297-799, 2014.
|
19 |
김태훈, 안현철, "A Hybrid Under-sampling Approach for Better Bankruptcy Prediction," 지능정보연구, 제21권, 제2호, pp.173-190, 2015.
DOI
|
20 |
N. Japkowicz, "The Class Imbalance Problem:Significance and Strategies," In Proceedings of the International Conference on Artificial Intelligence, pp.111-114, 2000.
|
21 |
N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, "SMOTE: Synthetic Minority Over-sampling Technique," Journal of Artificial Intelligence Research, Vol.16, pp.321-357, 2002.
DOI
|
22 |
이재동, 이지형, "데이터 불균형의 효과적인 학습을 위한 딥러닝 기법," 한국지능시스템학회 춘계학술대회 학술발표논문집, 제25권, 제1호, pp.113-114, 2015.
|
23 |
G. E. Batista, R. C. Prati, and M. C. Monard, "A Study of the Behavior of Several Methods for Balancing Machine Learning Training Data," ACM SIGKDD Explorations Newsletter, Vol.6, No.1, pp.20-29, 2004.
DOI
|