Performance Analysis of Data Mining Classification Techniques to Predict Diabetes

Procedia Computer Science

Volumn 82, Issue , 2016, Pages 115-121

  Perveen, Sajida ^a   Shahbaz, Muhammad ^a   Guergachi, Aziz ^b   Keshavjee, Karim ^c  

^a UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

^b RYERSON UNIVERSITY   (Canada)

^c UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Adaboost and Decision tree; Bagging; Base Learner; Diabetes Mellitus; Ensemble method

Indexed keywords

ADAPTIVE BOOSTING; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DECISION SUPPORT SYSTEMS; DECISION TREES; FORECASTING; SPACE DIVISION MULTIPLE ACCESS; TREES (MATHEMATICS);

BAGGING; BASE LEARNERS; CLINICAL DECISION SUPPORT SYSTEMS; DIABETES MELLITUS; ENSEMBLE METHODS; MINING CLASSIFICATION; PERFORMANCE ANALYSIS; SURVEILLANCE NETWORKS;

DATA MINING;

EID: 84994275591     PISSN: None     EISSN: 18770509     Source Type: Conference Proceeding    
DOI: 10.1016/j.procs.2016.04.016     Document Type: Conference Paper

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