期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：3
页码：179-184
DOI：10.14569/IJACSA.2019.0100323
出版社：Science and Information Society (SAI)
摘要：An examination of the ability of machine learning methodologies in classifying women Waterpipe (WP) smoker’s level of nicotine dependence is proposed in this work. In this study, we developed a classifier that predicts the level of nicotine dependence for WP tobacco female smokers using a set of novel features relevant to smokers including age, residency, and educational level. The evaluation results show that our approach achieves a recall of 82% when applied on a dataset of female WP smokers in Jordan.
