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 language | English (US) |
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Pages (from-to) | 171 |
Number of pages | 1 |
Journal | Neural Networks |
Volume | 1 |
Issue number | 1 SUPPL |
DOIs | |
State | Published - 1988 |
Event | International Neural Network Society 1988 First Annual Meeting - Boston, MA, USA Duration: Sep 6 1988 → Sep 10 1988 |