A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem

Authors:
Parag C. Pendharkar
Affiliations:
Information Systems, School of Business Administration, Pennsylvania State University at Harrisburg, Middletown, PA
Venue:
Computers and Operations Research
Year:
2005

Citing 15
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Abstract

We propose a threshold-varying artificial neural network (TV-ANN) approach for solving the binary classification problem. Using a set of simulated and real-world data set for bankruptcy prediction, we illustrate that the proposed TV-ANN fares well, both for training and holdout samples, when compared to the traditional backpropagation artificial neural network (ANN) and the statistical linear discriminant analysis. The performance comparisons of TV-ANN with a genetic algorithm-based ANN and a classification tree approach C4.5 resulted in mixed results.