- Title
- Application of optimisation-based data mining techniques to tobacco control dataset
- Creator
- Dzalilov, Zari; Zhang, J; Bagirov, Adil; Mammadov, Musa
- Date
- 2010
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/42103
- Identifier
- vital:4369
- Identifier
- ISSN:2146-0337
- Abstract
- Tobacco smoking is one of the leading causes of death around the world. Consequently, control of tobacco use is an important global public health issue. Tobacco control may be aided by development of theoretical and methodological frameworks for describing and understanding complex tobacco control systems. Linear regression and logistic regression are currently very popular statistical techniques for modeling and analyzing complex data in tobacco control systems. However, in tobacco markets, numerous interrelated factors nontrivially interact with tobacco control policies, such that policies and control outcomes are nonlinearly related.
- Relation
- International Journal of Lean Thinking Vol. 1, no. 1 (2010), p. 27-41
- Rights
- Copyright Yalin Dusance Solution Centre
- Rights
- This metadata is freely available under a CCO license
- Subject
- Tobacco control; Data mining; Global optimization; Feature selection; Linear least square fitting.
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