Classifier and cluster ensembles for mining concept drifting data streams

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2010, Pages 1175-1180

  Zhang, Peng ^a   Zhu, Xingquan ^b   Tan, Jianlong ^a   Guo, Li ^a  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^b UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Classification; Concept drifting; Data stream mining; Ensemble learning

Indexed keywords

BASE MODELS; CLASS LABELS; CLASSIFICATION; CLASSIFIER ENSEMBLES; CLUSTER ENSEMBLES; CONCEPT DRIFTING; DATA STREAM; DATA STREAM MINING; ENSEMBLE CLASSIFIERS; ENSEMBLE LEARNING; ENSEMBLE MODELS; INTERNAL STRUCTURE; INTRINSIC MERITS; LABEL PROPAGATION; LABOR INTENSIVE; PREDICTION MODEL; REAL WORLD DATA; STREAM DATA; STREAM DATA MINING; UNLABELED SAMPLES; WEIGHTED AVERAGES;

CLASSIFIERS; COMBINES; DATA COMMUNICATION SYSTEMS; HYDRAULICS; MATHEMATICAL MODELS;

DATA MINING;

EID: 79951740645     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2010.125     Document Type: Conference Paper

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