Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Considerations of the nature of the relationship between generalization and interpretability in evolutionary fuzzy systems|
|Citation:||Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), held in Dublin, Ireland, 12-16 July, 2011: pp.97-98|
|Conference Name:||Genetic and Evolutionary Computation Conference (13th : 2011 : Dublin, Ireland)|
|Adam Ghandar and Zbigniew Michalewicz|
|Abstract:||Performance out of sample is a clear determinant of the usefulness of any prediction model regardless of the application. Fuzzy knowledge base systems are also useful due to interpretability; this factor is often cited as an advantage over “black box” systems which make model verification by expert users more difficult. Here we examine additional advantages of interpretability for promoting general performance out side training data.|
|Keywords:||Evolutionary computation; fuzzy systems|
|Rights:||Copyright is held by the author/owner(s).|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.