Artificial Intelligence in Economics and Managment: An - download pdf or read online

By Phillip Ein-Dor

long ago many years a number of researchers have built statistical types for the prediction of company financial ruin, e. g. Altman (1968) and Bilderbeek (1983). A version for predicting company financial ruin goals to explain the relation among financial ruin and a couple of explanatory monetary ratios. those ratios will be calculated from the data contained in a company's annual document. The is to acquire a style for well timed prediction of financial disaster, a so­ final objective referred to as "early caution" method. extra lately, this topic has attracted the eye of researchers within the quarter of laptop studying, e. g. Shaw and Gentry (1990), Fletcher and Goss (1993), and Tam and Kiang (1992). This learn is mostly directed on the comparability of desktop studying tools, similar to induction of type timber and neural networks, with the "standard" statistical tools of linear discriminant research and logistic regression. In previous examine, Feelders et al. (1994) played an identical comparative research. The tools used have been linear discriminant research, choice timber and neural networks. We used an information set which contained 139 annual studies of Dutch commercial and buying and selling businesses. The experiments confirmed that the expected prediction blunders of either the choice tree and neural community have been lower than the anticipated blunders of the linear discriminant. therefore it appears we will achieve through changing the "traditionally" used linear discriminant through a extra versatile category option to are expecting company financial ruin. the information set utilized in those experiments was once very small however.

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Artificial Intelligence in Economics and Managment: An Edited Proceedings on the Fourth International Workshop: AIEM4 Tel-Aviv, Israel, January 8–10, 1996 by Phillip Ein-Dor


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