An efficient feature selection method for mobile devices with application to activity recognition

Neurocomputing

Volumn 74, Issue 17, 2011, Pages 3543-3552

  Peng, Jian Xun ^a   Ferguson, Stuart ^a   Rafferty, Karen ^a   Kelly, Paul D ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Activity recognition; Data classification; Feature selection algorithm; Mobile devices

Indexed keywords

ACCELEROMETER DATA; ACTIVITY RECOGNITION; CLASS LABELS; DATA CLASSIFICATION; EFFICIENT FEATURE SELECTIONS; FEATURE SELECTION ALGORITHM; FEATURE SELECTION METHODS; HUMAN ACTIVITY RECOGNITION; INFORMATIVENESS; MEMORY REQUIREMENTS; REGRESSION MODEL; SUBSET SELECTION; TRAINING PATTERNS; TRAINING PROCEDURES; TWO STAGE; VARIABLE SELECTION;

ACCELEROMETERS; ALGORITHMS; CLASSIFICATION (OF INFORMATION); MOBILE DEVICES; RANDOM ACCESS STORAGE; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

FEATURE EXTRACTION;

ACCELEROMETER; ARTICLE; CLASSIFICATION ALGORITHM; COMPUTER MEMORY; CONTROLLED STUDY; FEATURE SELECTION ALGORITHM; HUMAN ACTIVITIES; INFORMATION PROCESSING; INTERMETHOD COMPARISON; NONLINEAR REGRESSION ANALYSIS; PERSONAL DIGITAL ASSISTANT; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

EID: 80052932946     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.06.023     Document Type: Article

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