DocumentCode :
3853419
Title :
A representation theorem for linear pattern classifier training
Author :
Stevo Božinovski
Author_Institution :
Electrical Engineering Faculty, Karpoš
Issue :
1
fYear :
1985
Firstpage :
159
Lastpage :
161
Abstract :
A new representation concept, named the teaching space approach, for the pattern classification training theory is proposed as an alternative to the feature space and the weight space approach used in the contemporary pattern classification theory. The concept is introduced formally by means of a representation theorem. A model of the training process is given by the theorem that makes transparent the essential factors of the pattern classification training. This result is significant in the development of a theory of teaching systems, which is relevant to areas such as pattern recognition, neural networks, associative memories, robot training, and human training.
Keywords :
"Training","Prototypes","Pattern classification","Support vector machine classification","Vectors","Pattern recognition"
Journal_Title :
IEEE Transactions on Systems, Man, and Cybernetics
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/TSMC.1985.6313405
Filename :
6313405
Link To Document :
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