Dynamic Clustering Forest: An ensemble framework to efficiently classify textual data stream with concept drift

Information Sciences

Volumn 357, Issue , 2016, Pages 125-143

  Song, Ge ^a,b   Ye, Yunming ^b   Zhang, Haijun ^b   Xu, Xiaofei ^b   Lau, Raymond Y K ^c   Liu, Feng ^b  

^a SOUTH CHINA AGRICULTURAL UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

^c CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Clustering tree; Concept drift; Ensemble learning; Textual stream

Indexed keywords

DATA COMMUNICATION SYSTEMS; FORESTRY;

CLASSIFICATION METHODS; CLUSTERING TREES; CONCEPT DRIFTS; ENSEMBLE LEARNING; ENSEMBLE STRATEGIES; HIGH-DIMENSIONAL FEATURE SPACE; STREAM CLASSIFICATION; TEXTUAL STREAM;

MEAN SQUARE ERROR;

EID: 84964265088     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2016.03.043     Document Type: Article

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