Abstract: Usually,cost-sensitive learning assumes that different types of cost can be converted into a unified units of the same price.Apparently how to construct appropriate cost-sensitive attribute selection factor is a challenge．In this paper,a kind of heterogeneous cost-sensitive decision tree algorithm was designed,which fully considers the different cost in selecting split attribute,constructs an attribute selection model based on heterogeneous cost-sensitive,designs the price sensitive pruning strategy based on cost-sensitive．The experimental results show that this method is effective and more efficient than the present other methods．

Key words: Decision-tree classification,Cost-sensitive learning,Heterogeneous cost-sensitive