Tobacco Smoking Quality Evaluation Based on Cost-sensitive Bayesian Networks
Yingwu Chen · Jisuanji gongcheng · 2008
Bayesian networks have many merits which are applied in data mine,tobacco smoking quality is predicted and evaluated using Bayesian networks.But some important smoking quality has unequal classification cost.Cost-sensitivity Bayesian network is proposed accordingly. Structure of the cost-sensitivity Bayesian networks is learned using generative criterion.Then parameters of the cost-sensitivity Bayesian networks are evaluated based on cost-sensitivity loss function.A Bayesian network is learned to form a tobacco smoking quality dataset.Experimental results show that cost-sensitivity Bayesian network is feasible to evaluate tobacco smoking quality.