A decision tree approach for predicting smokers’ quit intentions

This paper presents a decision tree approach for predicting smokerspsila quit intentions using the data from the International Tobacco Control Four Country Survey. Three rule-based classification models are generated from three data sets using attributes in relation to demographics, warning labels, and smokerspsila beliefs. Both demographic attributes and warning label attributes are important in predicting smokerspsila quit intentions. The modelpsilas ability to predict smokerspsila quit intentions is enhanced, if the attributes regarding smokerspsila internal motivation and beliefs about quitting are included.