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

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

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Article ID: iaor20062704
Country: United Kingdom
Volume: 32
Issue: 10
Start Page Number: 2561
End Page Number: 2582
Publication Date: Oct 2005
Journal: Computers and Operations Research
Authors:
Keywords: forecasting: applications, neural networks, statistics: empirical
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.

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