Logical Second Order Models: Achieving Synergy Between Computer Power and Human Reason

Abstract

This research investigates computer generated hybrid second order models of two numerically based approaches to risk classification: logistic regression and neural networks. If-Then rules to assess bankruptcy risk were generated by a rule induction algorithm in three ways: (1) using actual bankruptcy as the criterion, (2) using a criterion based on a Logit… (More)
DOI: 10.1016/S0020-0255(98)10059-2

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@article{Gim1999LogicalSO, title={Logical Second Order Models: Achieving Synergy Between Computer Power and Human Reason}, author={Gwangyong Gim and Thomas Whalen}, journal={Inf. Sci.}, year={1999}, volume={114}, pages={81-104} }