Decision tree construction method based on rough set and distance function
Luo Qiu-jin · Jisuanji gongcheng yu sheji · 2008
Decision tree which is effectively used in the classification of data mining.On the decision tree construction algorithm,the core of condition attributes with respect to decision attributes in rough set theory is used for selection of attributes in multivariate tests.Considering the advantage and disadvantage of the decision trees and rough set,the decision trees and rough set are combined.A new multivariate decision tree construction algorithm is offered,which restricts each of nodes containing the number of attributes,and then,choice attributes combination according to the attribute dependability and De Mantaras distance function.The prominent merit of this al-gorithm is that it can reduce the height of a tree,and can raise readability of classing rules.