DocumentCode :
624534
Title :
Three-way decisions with artificial neural networks
Author :
Xiaofei Deng
Author_Institution :
Dept. of Comput. Sci., Univ. of Regina, Regina, SK, Canada
fYear :
2013
fDate :
5-8 May 2013
Firstpage :
1
Lastpage :
4
Abstract :
The theory of three-way decisions provides an additional option to the conventional two-way decisions that use only two options, namely, accepting or rejecting. The third option is called a non-commitment decision that usually means a decision in deferment or requiring further observations. Recent studies provide an evaluation-based framework of three-way decisions, in which one can make a decision according to evaluations. One of the fundamental issues of this framework is the interpretation and construction of evaluation functions. The Artificial Neural Networks (ANNs) provide a practical method of learning evaluation functions from the training data. Mutual benefits can be found in both theories. The theory of three-way decisions extends the ANNs to a three-valued output model, on the other hand, the ANNs provide a general approach to the construction of evaluations.
Keywords :
decision theory; learning (artificial intelligence); neural nets; ANN; accepting option; artificial neural network; evaluation function construction; evaluation function interpretation; evaluation-based framework; learning evaluation function; noncommitment decision; rejecting option; three-valued output model; three-way decision theory; two-way decision theory; Computers; Educational institutions; Neurons; Probabilistic logic; Rough sets; Training; Vectors; Three-way decisions; artificial neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2013 26th Annual IEEE Canadian Conference on
Conference_Location :
Regina, SK
ISSN :
0840-7789
Print_ISBN :
978-1-4799-0031-2
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2013.6567830
Filename :
6567830
Link To Document :
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