Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1349

 Title: Classiﬁcation of Smoking Cessation Status Using Various Data Mining Methods Authors: Kartelj, Aleksandar Keywords: Data MiningClassiﬁcationInduction 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 URI: http://hdl.handle.net/10525/1349 ISSN: 0205-3217 Appears in Collections: Mathematica Balkanica New Series, Vol. 24, 2010, Fasc. 3-4

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