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Application of data mining techniques for the pbkp_rediction of tobacco and alcohol use in university students

Abstract:

Tobacco addiction is a social health problem, reaching 30% of the adult population worldwide. For health organizations, it is essential to have tools that allow them to apply care and prevention policies. A pilot study is proposed to discover patterns of characteristics on tobacco and alcohol poli-consumers in university students. Thus, the information was collected from 478 Ecuadorian young university students, obtaining records of 73 socio-demographic, psychosocial, health and consumption variables. A method of data mining is applied for pbkp_rediction: pre-processing, sample analysis, application of algorithms and analysis of results. Seven variables with greater involvement in the pbkp_rediction are obtained, which are validated in two experiments, applying decision trees and neural networks.