Chain business distributed decision tree algorithm based on region-factor
JU Chun-hua · Systems Engineering - Theory & Practice · 2011
Chain business data have the feature of thedistributed heterogeneousandregional differences, which make the traditional decision tree algorithm is difficult to meet the requirements of cross-regional data mining.This paper analyzes impact features of the chain business network marketing behavior based on the different regional economic development level,size of population and other economic factors,puts forward introducing region-factor into distributed data mining module for the chain business;based on defining the concept of region-factor region factor,decision tree characteristics and characteristic differences rate,puts forward RDT algorithm which is made up of regional branch algorithm module,feature difference algorithm modules and branch store of the sub-tree construction algorithm module.Thought empirical analysis of a chain commercial group's branch stores which are in the cities of Hangzhou,Shaoxing,Ningbo,Wenzhou,Taizhou,Jinhua,Lishui,shows the algorithm is successfully applied to data mining process in a chain business enterprises.