In this paper, we improve the classification performance of categorical data using an Adoptive Hamming Distance. We defined the equivalent categorical values and showed how those categorical values were searched to adopt the distance. The effectiveness of the proposed method was demonstrated using various classification examples.
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Jae-Sung LEE, Dae-Won KIM, "Classifying Categorical Data Based on Adoptive Hamming Distance" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 1, pp. 189-192, January 2010, doi: 10.1587/transinf.E93.D.189.
Abstract: In this paper, we improve the classification performance of categorical data using an Adoptive Hamming Distance. We defined the equivalent categorical values and showed how those categorical values were searched to adopt the distance. The effectiveness of the proposed method was demonstrated using various classification examples.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.189/_p
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@ARTICLE{e93-d_1_189,
author={Jae-Sung LEE, Dae-Won KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Classifying Categorical Data Based on Adoptive Hamming Distance},
year={2010},
volume={E93-D},
number={1},
pages={189-192},
abstract={In this paper, we improve the classification performance of categorical data using an Adoptive Hamming Distance. We defined the equivalent categorical values and showed how those categorical values were searched to adopt the distance. The effectiveness of the proposed method was demonstrated using various classification examples.},
keywords={},
doi={10.1587/transinf.E93.D.189},
ISSN={1745-1361},
month={January},}
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TY - JOUR
TI - Classifying Categorical Data Based on Adoptive Hamming Distance
T2 - IEICE TRANSACTIONS on Information
SP - 189
EP - 192
AU - Jae-Sung LEE
AU - Dae-Won KIM
PY - 2010
DO - 10.1587/transinf.E93.D.189
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2010
AB - In this paper, we improve the classification performance of categorical data using an Adoptive Hamming Distance. We defined the equivalent categorical values and showed how those categorical values were searched to adopt the distance. The effectiveness of the proposed method was demonstrated using various classification examples.
ER -