A causal feature selection algorithm for stock prediction modeling

Neurocomputing

Volumn 142, Issue , 2014, Pages 48-59

  Zhang, Xiangzhou ^a   Hu, Yong ^b   Xie, Kang ^a   Wang, Shouyang ^c,d   Ngai, E W T ^e   Liu, Mei ^f  

^a SUN YAT SEN UNIVERSITY   (China)

^b GUANGDONG UNIVERSITY OF FOREIGN STUDIES   (China)

^c INSTITUTE OF SYSTEMS SCIENCE   (China)

^d UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^e HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^f University Heights   (United States)

Author keywords

Causal discovery; Data mining; Feature selection; Stock prediction; V structure

Indexed keywords

DATA MINING; DECISION TREES; FEATURE EXTRACTION; FORECASTING; PRINCIPAL COMPONENT ANALYSIS; PRODUCT DESIGN;

ACCURACY AND PRECISION; CAUSAL DISCOVERY; COMPARATIVE EXPERIMENTS; FEATURE SELECTION ALGORITHM; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATORS; SHANGHAI STOCK EXCHANGES; STOCK PREDICTIONS; V-STRUCTURE;

ALGORITHMS;

ACCURACY; ALGORITHM; ARTICLE; CAUSAL FEATURE SELECTION ALGORITHM; COMPUTER ANALYSIS; COMPUTER MODEL; COMPUTER PREDICTION; CONTROLLED STUDY; DECISION TREE; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR; MATHEMATICAL ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROCESS DEVELOPMENT; SOCIAL MARKETING; STOCKPREDICTION;

EID: 84904356230     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.01.057     Document Type: Article

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