Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers
Kybernetika (1998)
- Volume: 34, Issue: 4, page [405]-410
- ISSN: 0023-5954
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topFerri, Francesc J.. "Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers." Kybernetika 34.4 (1998): [405]-410. <http://eudml.org/doc/33369>.
@article{Ferri1998,
abstract = {Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along with some suggestions for their joint application in some cases.},
author = {Ferri, Francesc J.},
journal = {Kybernetika},
keywords = {nearest neighbour classification; prototype selection; nearest neighbour classification; prototype selection},
language = {eng},
number = {4},
pages = {[405]-410},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers},
url = {http://eudml.org/doc/33369},
volume = {34},
year = {1998},
}
TY - JOUR
AU - Ferri, Francesc J.
TI - Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers
JO - Kybernetika
PY - 1998
PB - Institute of Information Theory and Automation AS CR
VL - 34
IS - 4
SP - [405]
EP - 410
AB - Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along with some suggestions for their joint application in some cases.
LA - eng
KW - nearest neighbour classification; prototype selection; nearest neighbour classification; prototype selection
UR - http://eudml.org/doc/33369
ER -
References
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