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检索条件"主题词=K2 algorithm"
33 条 记 录,以下是1-10 订阅
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An efficient node ordering method using the conditional frequency for the k2 algorithm
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PATTERN RECOGNITION LETTERS 2014年 第1期40卷 80-87页
作者: ko, Song kim, Dae-Won Chung Ang Univ Sch Comp Sci & Engn Seoul 156756 South Korea
In Bayesian networks, the k2 algorithm is one of the most effective structure-learning methods. However, because the performance of the k2 algorithm depends on node ordering, more effective node ordering inference met... 详细信息
来源: 评论
Operational failure analysis of high-speed electric multiple units: A Bayesian network-k2 algorithm-expectation maximization approach
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RELIABILITY ENGINEERING & SYSTEM SAFETY 2021年 205卷 107250-107250页
作者: Huang, Wencheng kou, Xingyi Zhang, Yue Mi, Rongwei Yin, Dezhi Xiao, Wei Liu, Zhanru Southwest Jiaotong Univ Sch Transportat & Logist China 611756 Sichuan Peoples R China Southwest Jiaotong Univ Inst Syst Sci & Engn Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Natl United Engn Lab Intergrated & Intelligent Tr Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Natl Engn Lab Integrated Transportat Big Data App Chengdu 611756 Sichuan Peoples R China China Railway Eryuan Engn Grp Co LTD China 610031 Sichuan Peoples R China
In this paper, a Bayesian Network-k2 algorithm-Expectation Maximization (BN-k2-EM) approach is proposed to quantify the intensity of coupling influence among the operational failures and find out the specific failure ... 详细信息
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Improved Bayesian Network Structure Learning with Node Ordering via k2 algorithm
Improved Bayesian Network Structure Learning with Node Order...
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10th International Conference on Intelligent Computing (ICIC)
作者: Wei, Zhongqiang Xu, Hongzhe Li, Wen Gui, Xiaolin Wu, Xiaozhou Xi An Jiao Tong Univ Shaanxi Key Lab Comp Network Xian 710049 Peoples R China
The precise construction of Bayesian network classifier from database is an NP-hard problem and still one of the most exciting challenges. k2 algorithm can reduce search space effectively, improve learning efficiency,... 详细信息
来源: 评论
A New Approach for Bayesian Classifier Learning Structure via k2 algorithm
A New Approach for Bayesian Classifier Learning Structure vi...
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8th International Conference on Intelligent Computing (ICIC)
作者: Bouhamed, Heni Masmoudi, Afif Lecroq, Thierry Rebai, Ahmed Univ Rouen LITIS EA 4108 1 Rue Thomas Becket F-76821 Mont St Aignan France Fac Sci Sfax Dept Math Sfax Tunisia Ctr Biotechnol Sfax Bioinformat Unit Sfax Tunisia
It is a well-known fact that the Bayesian Networks' (BNs) use as classifiers in different fields of application has recently witnessed a noticeable growth. Yet, the Naive Bayes' application, and even the augme... 详细信息
来源: 评论
A Simple Node Ordering Method for the k2 algorithm based on the Factor Analysis  6
A Simple Node Ordering Method for the K2 Algorithm based on ...
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6th International Conference on Pattern Recognition Applications and Methods (ICPRAM)
作者: Tabar, Vahid Rezaei Allameh Tabatabai Univ Dept Stat Fac Math & Comp Sci Tehran Iran
In this paper, we use the Factor Analysis (FA) to determine the node ordering as an input for k2 algorithm in the task of learning Bayesian network structure. For this purpose, we use the communality concept in factor... 详细信息
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Expectation maximization based ordering aggregation for improving the k2 structure learning algorithm
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INTELLIGENT DATA ANALYSIS 2015年 第5期19卷 1003-1018页
作者: Amirkhani, Hossein Rahmati, Mohammad Amirkabir Univ Technol Comp Engn & Informat Technol Dept Tehran Iran
Some of the basic algorithms for learning the structure of Bayesian networks, such as the well-known k2 algorithm, require a prior ordering over the nodes as part of the input. It is well known that the accuracy of th... 详细信息
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Reliabilities analysis of evacuation on offshore platforms: A dynamic Bayesian Network model
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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2021年 150卷 179-193页
作者: Wang, Yanfu Wang, kun Wang, Tao Li, Xi Yan khan, Fasial Yang, Zaili Wang, Jin China Univ Petr Coll Mech & Elect Engn Dept Safety Sci & Engn Qingdao Peoples R China Liverpool John Moores Univ Liverpool Logist Offshore & Marine LOOM Res Inst Liverpool Merseyside England Mem Univ Newfoundland Fac Engn & Appl Sci Ctr Risk Integr & Safety Engn C RISE St John NF A1B 3X5 Canada
An offshore platform is naturally vulnerable to accidents, such as the leakage of dangerous chemicals, fire and explosion. Oil and gas are explosive and all the equipment and pipes are squeezed into a limited area on ... 详细信息
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Classification of fluorescence in situ hybridization images using belief networks
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PATTERN RECOGNITION LETTERS 2004年 第16期25卷 1777-1785页
作者: Malka, R Lerner, B Ben Gurion Univ Negev Dept Elect & Comp Engn Pattern Anal & Machine Learning Lab IL-84105 Beer Sheva Israel
The structure and parameters of a belief network are learned in order to classify images enabling the detection of genetic abnormalities. We compare a structure learned from the data to another structure obtained util... 详细信息
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A missing value imputation method using a Bayesian network with weighted learning
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ELECTRONICS AND COMMUNICATIONS IN JAPAN 2012年 第12期95卷 1-9页
作者: Miyakoshi, Yoshihiro kato, Shohei Nagoya Inst Technol Nagoya Aichi Japan
With the development of computer networks, it has become easy to have huge databases. Accordingly, it is becoming difficult for users to extract knowledge from such databases. In this paper we focus on data mining, es... 详细信息
来源: 评论
Construction of Customer Classification Model Based on Bayesian Network
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JOURNAL OF COMPUTERS 2013年 第5期8卷 1200-1206页
作者: Zhu, Qian Zhang, Yingying Hebei Finance Univ Dept Econ & Business Baoding 071051 Peoples R China
At present, the researches on customer segmentation model based on Bayesian network are few. This paper makes a research on the classification problems based on Bayesian network. First of all, it used literature searc... 详细信息
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