A causal analysis for the expenditure data of business travelers

Determining the causal relation among attributes in a domain<br />is a key task in the data mining and knowledge discovery. In this<br />paper, we applied a causal discovery algorithm to the business traveler<br />expenditure survey data [1]. A general class of causal models is adopted in<br />this paper to discover the causal relationship among continuous and discrete variables. All those factors which have direct effect on the expense<br />pattern of travelers could be detected. Our discovery results reinforced<br />some conclusions of the rough set analysis and found some new conclusions which might significantly improve the understanding of expenditure behaviors of the business traveler.<br />