Markov-Miml: A Markov chain-based multi-instance multi-label learning algorithm

Knowledge and Information Systems

Volumn 37, Issue 1, 2013, Pages 83-104

  Wu, Qingyao ^a,b   Ng, Michael K ^c   Ye, Yunming ^a,b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b Shenzhen Key Laboratory of Internet Information Collaboration   (China)

^c HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

Label ranking; Markov chain; Multi instance multi label data; Stationary probability distribution; Transition probability matrix

Indexed keywords

MARKOV CHAINS; PROBABILITY DISTRIBUTIONS; SUPPORT VECTOR MACHINES;

CLASSIFICATION PERFORMANCE; COMPUTATIONAL TIME; COMPUTATIONALLY EFFICIENT; LABEL RANKINGS; MULTI-INSTANCE MULTI-LABEL LEARNING; MULTI-LABEL; MULTIPLE INSTANCES; TRANSITION PROBABILITY MATRIX;

LEARNING ALGORITHMS;

EID: 84884593174     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-012-0567-9     Document Type: Article

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