Aarts, E.H.L., Zwietering, P.J., & Wessels, J. (1992). Exact Classification with Two-Layered Perceptrons. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-92-049
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Abstract
We study the capabilities of two-layered perceptrons for classifying exactly a given subset. Both necessary and sufficient conditions are derived for subsets to be exactly classifiable with two-layered perceptrons that use the hard-limiting response function. The necessary conditions can be viewed as generalizations of the linear-separability condition of one-layered perceptrons and confirm the conjecture that the capabilities of two-layered perceptrons are more limited than those of three-layered perceptrons. The sufficient conditions show that the capabilities of two-layered perceptrons extend beyond the exact classification of convex subsets. Furthermore, we present an algorithmic approach to the problem of verifying the sufficiency condition for a given subset.
Item Type: | Monograph (IIASA Working Paper) |
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Research Programs: | Methodology of Decision Analysis (MDA) |
Depositing User: | IIASA Import |
Date Deposited: | 15 Jan 2016 02:01 |
Last Modified: | 27 Aug 2021 17:14 |
URI: | https://pure.iiasa.ac.at/3649 |
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