The handling of don't care attributes
Resource
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Journal
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Pages
-
Date Issued
1991-11
Date
1991-11
Author(s)
Lee, Hahn-Ming
Hsu, Ching-Chi
DOI
N/A
Abstract
A critical factor that affects the performance of neural network training algorithms and the generalization of trained networks is the training instances. The authors consider the handling of don't care attributes in training instances. Several approaches are discussed and their experimental results are presented. The following approaches are considered: (1) replace don't care attributes with a fixed value; (2) replace don't care attributes with their maximum or minimum encoded values; (3) replace don't care attributes with their maximum and minimum encoded values; and (4) replace don't care attributes with all their possible encoded values.
SDGs
Type
journal article
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