DocumentCode
394404
Title
Extending ETL for multi-class output
Author
Chaudhari, Narendra S. ; Tiwari, Aruna
Author_Institution
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
Volume
4
fYear
2002
fDate
18-22 Nov. 2002
Firstpage
1777
Abstract
We present a method for extending the expand and truncate learning (ETL) technique for multi-class output. Kim and Park (1995) have given two hints for solving the same problem, but their hints may result in a large sized neural net. Here, we propose another method for the same problem, which is expected to result in a smaller neural net. Our method is based on yet other known technique introduced by Gray and Michel (1992), called the Boolean like training algorithm.
Keywords
Boolean functions; learning (artificial intelligence); neural nets; Boolean algebra; Boolean like training algorithm; expand and truncate learning; multiclass output; neural net; Convergence; Hamming distance; Logic; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN
981-04-7524-1
Type
conf
DOI
10.1109/ICONIP.2002.1198979
Filename
1198979
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