Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/1487
Title: A New Variable Ordering Method for the K2 Algorithm
Authors: Uzbaş, Betül
Arslan, Ahmet
Keywords: NETWORKS
Issue Date: 2020
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Abstract: K2 is an algorithm used for learning the structure of a Bayesian networks (BN). The performance of the K2 algorithm depends on the order of the variables. If the given ordering is not sufficient, the score of the network structure is found to be low. We proposed a new variable ordering method in order to find the hierarchy of the variables. The proposed method was compared with other methods by using synthetic and real-world data sets. Experimental results show that the proposed method is efficient in terms of both time and score.
Description: International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME) -- APR 20-22, 2019 -- Antalya, TURKEY
URI: https://doi.org/10.1007/978-3-030-36178-5_3
https://hdl.handle.net/20.500.13091/1487
ISBN: 978-3-030-36178-5; 978-3-030-36177-8
ISSN: 2367-4512
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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