The nature of statistical learning theory
The nature of statistical learning theory
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Bankruptcy prediction by generalized additive models: Research Articles
Applied Stochastic Models in Business and Industry
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
An integrative model with subject weight based on neural network learning for bankruptcy prediction
Expert Systems with Applications: An International Journal
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
A genetic programming model for bankruptcy prediction: Empirical evidence from Iran
Expert Systems with Applications: An International Journal
Failure prediction of dotcom companies using hybrid intelligent techniques
Expert Systems with Applications: An International Journal
A binary classification method for bankruptcy prediction
Expert Systems with Applications: An International Journal
A selective ensemble based on expected probabilities for bankruptcy prediction
Expert Systems with Applications: An International Journal
Feature selection in bankruptcy prediction
Knowledge-Based Systems
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
Bankruptcy prediction with neural logic networks by means of grammar-guided genetic programming
Expert Systems with Applications: An International Journal
Forecasting corporate bankruptcy with an ensemble of classifiers
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Clustering and visualization of bankruptcy trajectory using self-organizing map
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Partial Least Square Discriminant Analysis for bankruptcy prediction
Decision Support Systems
A loan default discrimination model using cost-sensitive support vector machine improved by PSO
Information Technology and Management
Expert Systems with Applications: An International Journal
PLS-based recursive feature elimination for high-dimensional small sample
Knowledge-Based Systems
| Hi-index | 12.06 |
The evaluation of corporate financial distress has attracted significant global attention as a result of the increasing number of worldwide corporate failures. There is an immediate and compelling need for more effective financial distress prediction models. This paper presents a novel method to predict bankruptcy. The proposed method combines the partial least squares (PLS) based feature selection with support vector machine (SVM) for information fusion. PLS can successfully identify the complex nonlinearity and correlations among the financial indicators. The experimental results demonstrate its superior predictive ability. On the one hand, the proposed model can select the most relevant financial indicators to predict bankruptcy and at the same time identify the role of each variable in the prediction process. On the other hand, the proposed model's high levels of prediction accuracy can translate into benefits to financial organizations through such activities as credit approval, and loan portfolio and security management.