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
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;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938491
