Using neural networks for generalization problems

Soumitra Dutta, Shashi Shekhar

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper investigates if neural networks can be used for generalization problems. Generalization problems can be solved by conventional mathematical models or rule-based expert systems if the underlying application domain has complete or partial models. But it is difficult to solve generalization problems, when the problem domain lacks a domain model (we name those as non-conservative domains), e.g., the problem of assigning ratings to corporate bonds. In this paper we explore the application of neural networks in such non-conservative domains. We choose the ratings of corporate bonds as the practical domain for this study because of its enormous importance in the real world of finance.

Original languageEnglish (US)
Number of pages1
JournalNeural Networks
Volume1
Issue number1 SUPPL
DOIs
StatePublished - Jan 1 1988
EventInternational Neural Network Society 1988 First Annual Meeting - Boston, MA, USA
Duration: Sep 6 1988Sep 10 1988

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