Classifying and predicting instances for smoking cessation management system (Smoke mind)
Abdullah H. Alsharif, Nada Y. Philip · 2016
Smoking is one of the major activities that can become highly addictive and can cause major health-related risks. It is one of the major causes of death worldwide. There are various issues revolving around smoking and its complications. To assess the impact of smoking, its complications, and the process of achieving smoking cessation, an online survey was conducted. In this study, the results of the survey are used as a dataset to which various data mining classification techniques are applied. The study has found that the Naïve Bayes algorithm gives the best performance on the survey data with an accuracy of 84.713 and an execution time of 0.11 seconds, followed by J48 and Logistic Regression.