A Combination of Two Classification Techniques for Businesses Bankruptcy Prediction

4 Pages Posted: 24 Dec 2009

See all articles by Ioan Andone

Ioan Andone

Alexandru Ioan Cuza University - Faculty of Economics and Business Administration

Napoleon-Alexandru Sireteanu

"Alexandru Ioan Cuza" University of Iasi, Faculty of Economics and Business Administration, Business Information Systems

Date Written: December 24, 2009

Abstract

The scientific community has demonstrated that for the bankruptcy prediction, different techniques have different advantages on different data sets and different feature selection approaches. This subject has attracted a lot of research interests as it is one of the major preoccupation of accounting specialists, business analysts and information systems developers. Because there is no prediction performance via the techniques of artificial neural networks, we have explored this topic, and divided the prediction performance using different techniques into two important parts: 1) bankruptcy prediction and 2) non-bankruptcy prediction. In this short paper, we have built a combination of two well known classification techniques, namely the decision tree and the back propagation neural network. In our opinion, this combination (hybridization technique) provides an approach which inherits advantages and avoids disadvantages of different classification techniques. We described the research results, and demonstrated our expectations.

Keywords: prediction, artificial intelligence applications, decision trees, neural networks, hybridization

JEL Classification: G33, M21

Suggested Citation

Andone, Ioan and Sireteanu, Napoleon-Alexandru, A Combination of Two Classification Techniques for Businesses Bankruptcy Prediction (December 24, 2009). Available at SSRN: https://ssrn.com/abstract=1527726 or http://dx.doi.org/10.2139/ssrn.1527726

Ioan Andone

Alexandru Ioan Cuza University - Faculty of Economics and Business Administration ( email )

Bd. Carol I no.22
Iasi, RO-700505
Romania

Napoleon-Alexandru Sireteanu (Contact Author)

"Alexandru Ioan Cuza" University of Iasi, Faculty of Economics and Business Administration, Business Information Systems ( email )

Carol I Blvd, Nr.11
Lasi, 700506
Romania
400232201658 (Phone)

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