Study on Tourism Emergency Attribute Reduction Based on Rough Set

This paper describes attribute extraction, attribute classification and data cleaning process in tourism emergency, builds a widely applicable decision table, and uses the attribute reduction algorithm based on the importance of Pawlak property. The results proves that the decision table after reduction is more beneficial to obtain useful decision rules, on the premise of maintaining constant dependence of condition attributes and decision attributes.