End-user feature labeling: Supervised and semi-supervised approaches based on locally-weighted logistic regression

Artificial Intelligence

Volumn 204, Issue , 2013, Pages 56-74

  Das, Shubhomoy ^a   Moore, Travis ^a   Wong, Weng Keen ^a   Stumpf, Simone ^b   Oberst, Ian ^a   McIntosh, Kevin ^a   Burnett, Margaret ^a  

^a OREGON STATE UNIVERSITY   (United States)

^b CITY UNIVERSITY   (United Kingdom)

Author keywords

Feature labeling; Intelligent interfaces; Locally weighted logistic regression; Machine learning; Semi supervised learning

Indexed keywords

FEATURE LABELING; INTELLIGENT INTERFACE; LOGISTIC REGRESSIONS; QUALITY FEATURES; SEMI-SUPERVISED; SEMI-SUPERVISED ALGORITHM; SEMI-SUPERVISED LEARNING; UNLABELED DATA;

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; REGRESSION ANALYSIS; SUPERVISED LEARNING;

LEARNING ALGORITHMS;

EID: 84884253807     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2013.08.003     Document Type: Article

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