The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous abordons le problème du calcul de différents types de tests expressifs pour les arbres de décision et les arbres de régression. L’utilisation de tests expressifs est prometteuse, car elle peut améliorer la précision des prévisions des arbres et peut également nous fournir des indications sur les découvertes scientifiques. L’inconvénient est que le calcul d’un test optimal pourrait être coûteux. Nous présentons un cadre unifié pour aborder ce problème, et nous revisitons la conception d'algorithmes efficaces pour calculer des cas particuliers importants. Nous prouvons également qu’il est difficile de calculer une conjonction ou une disjonction optimale.
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Shinichi MORISHITA, Akihiro NAKAYA, "Expressive Tests for Classification and Regression" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 1, pp. 52-60, January 2000, doi: .
Abstract: We address the problem of computing various types of expressive tests for decision trees and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees, and it may also provide us some hints on scientific discovery. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or disjunction.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_1_52/_p
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@ARTICLE{e83-d_1_52,
author={Shinichi MORISHITA, Akihiro NAKAYA, },
journal={IEICE TRANSACTIONS on Information},
title={Expressive Tests for Classification and Regression},
year={2000},
volume={E83-D},
number={1},
pages={52-60},
abstract={We address the problem of computing various types of expressive tests for decision trees and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees, and it may also provide us some hints on scientific discovery. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or disjunction.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Expressive Tests for Classification and Regression
T2 - IEICE TRANSACTIONS on Information
SP - 52
EP - 60
AU - Shinichi MORISHITA
AU - Akihiro NAKAYA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2000
AB - We address the problem of computing various types of expressive tests for decision trees and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees, and it may also provide us some hints on scientific discovery. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or disjunction.
ER -