Empirical study of decision trees and ensemble classifiers for monitoring of diabetes patients in pervasive healthcare

Proceedings of the 2012 15th International Conference on Network-Based Information Systems, NBIS 2012

Volumn , Issue , 2012, Pages 441-446

  Kelarev, A V ^a   Stranieri, A ^a   Yearwood, J L ^a   Jelinek, H F ^b  

^a UNIVERSITY OF BALLARAT   (Australia)

^b CHARLES STURT UNIVERSITY   (Australia)

Author keywords

decision trees; ensemble classifiers

Indexed keywords

CHARLES STURT UNIVERSITIES; CLINICAL COMPLICATIONS; CONSENSUS FUNCTIONS; DIABETES PATIENTS; EMPIRICAL INVESTIGATION; EMPIRICAL STUDIES; ENSEMBLE CLASSIFIERS; ENSEMBLE METHODS; HEALTH MONITORING; NOVEL APPLICATIONS; PERFORMANCE PARAMETERS; PERVASIVE HEALTHCARE; RESEARCH INITIATIVES; RESOURCE AWARE; SENSOR DATA; WEARABLE SENSORS;

DATA HANDLING; EXPERIMENTS; FORESTRY; HEALTH CARE; INFORMATION SYSTEMS; SENSORS;

DECISION TREES;

CLASSIFICATION; DATA PROCESSING; DECISION MAKING; FORESTRY; HEALTH; SENSORS;

EID: 84870781792     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NBiS.2012.20     Document Type: Conference Paper

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