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Elsevier电子期刊(32)

在“Elsevier电子期刊”中，命中：32条，耗时：0.0389778 秒

在所有数据库中总计命中：99条

1.Sequential data feature selection for human motion recognition via Markov blanket

作者：Hongjun Zhou^a ; Mingyu You ; ^a ; ^{zhouhongjun@dynavisiontek.com} ; ^{myyou@tongji.edu.cn} ; Lei Liu^b ; Chao Zhuang^a

关键词：Sequential data ; Feature selection ; Markov blanket

刊名：Pattern Recognition Letters

出版年：2017

2.Wrapper-based gene selection with Markov blanket

作者：Aiguo Wang^a ; ^{wangaiguo2546@163.com}Author Vitae ; Ning An^a ; ^{ning.g.an@acm.org}Author Vitae ; Jing Yang^a ; ^{jsjyj0801@163.com}Author Vitae ; Guilin Chen^b ; ^{glchen@chzu.edu.cn}Author Vitae ; Lian Li^a ; ^{llian@hfut.edu.cn}Author Vitae ; Gil Alterovitz^c ; ^d ; ^e ; ^{gil_alterovitz@hms.harvard.edu}Author Vitae

关键词：Gene selection ; Microarray data ; Symmetric uncertainty ; Markov blanket ; Wrapper methods

刊名：Computers in Biology and Medicine

出版年：2017

3.Efficient score-based Markov Blanket discovery

作者：Tian Gao^a ; ^{tgao@us.ibm.com} ; Qiang Ji^b ; ^jiq@rpi.edu

关键词：Markov Blanket discovery ; Bayesian network ; Local structure learning

刊名：International Journal of Approximate Reasoning

出版年：2017

4.An efficient semi-supervised representatives feature selection algorithm based on information theory

作者：Yintong Wang^a ; ^b ; ^{wangyintong@nuaa.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Jiandong Wang^bAuthor Vitae ; Hao Liao^c ; ^{jamesliao520@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Haiyan Chen^bAuthor Vitae

关键词：Feature selection ; Markov blanket ; Information theory ; Semi-supervised learning ; Representative features

刊名：Pattern Recognition

出版年：2017

5.A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

作者：John F. Carriger^a ; Todd M. Martin^b ; Mace G. Barron^a ; ^{barron.mace@epa.gov" class="auth_mail" title="E-mail the corresponding author}

关键词：Mode of action ; Aquatic toxicity ; Bayesian network ; Markov blanket ; Chemical descriptors

刊名：Aquatic Toxicology

出版年：2016

6.High-dimensional feature selection via feature grouping: A Variable Neighborhood Search approach

作者：Miguel Garcí ; a-Torres ; ^a ; ^{mgarciat@upo.es" class="auth_mail" title="E-mail the corresponding author} ; Francisco Gó ; mez-Vela^a ; ^{fgomez@upo.es" class="auth_mail" title="E-mail the corresponding author} ; Belé ; n Meliá ; n-Batista^b ; ^{mbmelian@ull.es" class="auth_mail" title="E-mail the corresponding author} ; J. Marcos Moreno-Vega^b ; ^{jmmoreno@ull.es" class="auth_mail" title="E-mail the corresponding author}

关键词：Feature selection ; High dimensionality ; Metaheuristic ; Feature grouping

刊名：Information Sciences

出版年：2016

7.Hybridising harmony search with a Markov blanket for gene selection problems

作者：Salam Salameh Shreem ; Salwani Abdullah ; Mohd Zakree Ahmad Nazri

关键词：Gene selection ; Filter approach ; Harmony search algorithm ; Markov blanket ; Wrapper approach

刊名：Information Sciences

出版年：10 February, 2014

8.Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson¡¯s Disease Questionnaire (PDQ-39)

作者：Hanen Borchani^a ; ^{hanen.borchani@upm.es} ; Concha Bielza^a ; Pablo Mart?´ ; nez-Mart?´ ; n^b ; Pedro Larrañ ; aga^a

关键词：Multi-dimensional Bayesian network classifiers ; Markov blanket ; Multi-dimensional classification ; Parkinson&rsquo ; s disease ; EQ-5D ; PDQ-39

刊名：Journal of Biomedical Informatics

出版年：2012

9.Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers

作者：Hanen Borchani^a ; ^{hanen.borchani@upm.es} ; Concha Bielza^a ; ^{mcbielza@fi.upm.es} ; Carlos Toro^b ; ^{carlos.toro@salud.madrid.org} ; Pedro Larrañ ; aga^a ; ^{pedro.larranaga@fi.upm.es}

关键词：Multi-dimensional Bayesian network classifiers ; Markov blanket ; Human immunodeficiency virus ; Protease inhibitors ; Reverse transcriptase inhibitors

刊名：Artificial Intelligence in Medicine

出版年：2013

10.Discovering and orienting the edges connected to a target variable in a DAG via a sequential local learning approach

作者：Changzhang Wang^a ; ^{changzhang@pku.edu.cn" class="auth_mail} ; You Zhou^b ; ^{zy1314526@yahoo.cn" class="auth_mail} ; Qiang Zhao^c ; ^{zhaoqmath@gmail.com" class="auth_mail} ; Zhi Geng^a ; ^{zhigeng@pku.edu.cn" class="auth_mail} ; ^{zgeng@math.pku.edu.cn" class="auth_mail}

关键词：Causal network ; Directed acyclic graph ; Discover causes and effects ; Sequential structural learning

刊名：Computational Statistics and Data Analysis

出版年：September 2014

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