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Title: Classification of Smoking Cessation Status Using Various Data Mining Methods
Authors: Kartelj, Aleksandar
Keywords: Data Mining
Induction Learning
Issue Date: 2010
Publisher: Bulgarian Academy of Sciences - National Committee for Mathematics
Citation: Mathematica Balkanica New Series, Vol. 24, Fasc 3-4 (2010), 199p-205p
Abstract: This study examines different approaches of binary classification applied to the prob- lem of making distinction between former and current smokers. Prediction is based on data collected in national survey performed by the National center for health statistics of America in 2000. The process consists of two essential parts. The first one determines which attributes are relevant to smokers status, by using methods like basic genetic algorithm and different evaluation functions [1]. The second part is a classification itself, performed by using methods like logistic regression, neural networks and others [2]. Solving these types of problems has its real contributions in decision support systems used by some health institutions.
Description: AMS Subj. Classification: 62P10, 62H30, 68T01
ISSN: 0205-3217
Appears in Collections:Mathematica Balkanica New Series, Vol. 24, 2010, Fasc. 3-4

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