Interpretable decision sets: A joint framework for description and prediction

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 13-17-August-2016, Issue , 2016, Pages 1675-1684

  Lakkaraju, Himabindu ^a   Bach, Stephen H ^a   Leskovec, Jure ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BEHAVIORAL RESEARCH; COMPUTATIONAL EFFICIENCY; DATA MINING; DECISION MAKING;

AUTOMATIC DECISION; DECISION BOUNDARY; MACHINE LEARNING TECHNIQUES; MULTIPLE CHOICE QUESTIONS; OBJECTIVE FUNCTIONS; PREDICTIVE MODELS; RULE-BASED MODELS; SUBMODULAR FUNCTIONS;

LEARNING SYSTEMS;

EID: 84984941684     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2939672.2939874     Document Type: Conference Paper

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