Investigating Tobacco Usage Habits Using Data Mining Approach
Ključne riječi:
smokers, habits, tobacco, cigarettes, data mining, WEKA, J48 algorithm, decision treesSažetak
What are smokers’ habits today? Do people rather enjoy cigarettes or rolling tobacco? The research made for this study is going to give us the answer on these questions. The main reason which determines smokers’ habits is their lifestyle, e.g. it depends whether they are providing enough money for cigarettes because rolling tobacco is noticeable cheaper. The research is fulfilled by participants of different years, employment status and other lifestyle habits. The research will present the smoking habits of respondents conducted through data mining. The data are processed in the Weka software with the help of a decision tree method - to be precise, the J48 algorithm.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Reference
Bhargava, N., Sharma, G., Bhargava, R., Mathuria, M. (2013), “Decision Tree Analysis on J48 Algorithm for Data Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3 No. 6, pp. 1114-1119.
Dahan, H., Cohen, S., Rokach, L., Maimon, O. (2014), “Proactive data mining with decision trees”, Springer-Verlag, New York.
Folorunsho, O. (2013), „Comparative Study of Different Data Mining Techniques Performance in knowledge Discovery from Medical Database”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3 No. 3, pp. 11-15.
Padhye, A. (2006), “Natural Language Processing”, Duluth: University of Minnesota, USA.
Palace, B. (1996), “What is data mining”, Los Angeles: Anderson Graduate School of Management at UCLA, USA.
Sakoman, S., Kuzman, M., Šakić, V. (1997), “Pušačke navike zagrebačkih srednjoškolaca” [Smoking Habits of the High School Pupils in Zagreb], Društ. Istraž. Zagreb, Vol. 30-31 No. 4, pp. 513-535.
Sayad, S. (2011), „Real time data mining“, Cambridge Ontario: Self-Help Publishers, USA.
Two Crows Corporation (2005), „Introduction to Data mining and knowledge discovery”, 3rd ed., USA.
Witten, I.H. (2011), “Data mining: Practical machine learning tools and techniques”, Burlington: Morgan Kaufmann Publishers, USA.
WHO (2015), World Health Organization, available at: http://www.who.int (accessed June 26th 2015).
