DocumentCode
1748842
Title
A nearest neighbour rule with class membership (NNRC) for modelling problems
Author
van der Merwe, N.T. ; Hoffman, Anthony J. ; Stander, C. ; Heyns, S.P.
Author_Institution
Sch. for Electr. & Electron. Eng., Potchefstroom Univ. for CHE, South Africa
Volume
3
fYear
2001
fDate
2001
Firstpage
2104
Abstract
The nearest neighbour rule (NNR) has been used widely to determine a bound on the performance of classifiers. It has been shown that the error rate of the nearest neighbour classifier bounds the optimal Bayes error rate by a factor of at most two. We present NNRC, a nearest neighbour rule with class membership, to model the multiple fault conditions on a test rig. The NNR rule can be used only for classification problems. Hence we extend the NNR with NNRC to allow the use of continuous class labels as well
Keywords
fault diagnosis; neural nets; pattern classification; continuous class labels; modelling problems; multiple fault conditions; nearest neighbour classifier; nearest neighbour rule with class membership; optimal Bayes error rate; test rig; Africa; Cellular neural networks; Channel hot electron injection; Data mining; Error analysis; Fuzzy logic; Mechanical engineering; Neural networks; Recurrent neural networks; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.938491
Filename
938491
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