Construction and Implementution of Minimum Cost Decision Tree Based on Multi-Objective Optimization
CAO Liyuan
LI Shenluo
Abstract：A multi-objective optimization based on the cost sensitive decision tree building method is proposed. The misclassi?fication cost,test cost,waiting time cost and information gain rate as four optimization goal,the method of linear weighting is used to transfer the multi-objective optimization problem into single objective optimization problem,as the splitting attribute selection cri?terion. And then the concrete strategy of building the minimum cost decision tree and a hybrid testing decision tree method are put forward. Finally,the algorithm and two other algorithms in two real datasets are used to build decision trees and test the trees,and experimental results show that the decision tree obtained by this method has a smaller cost,more efficient and stronger generaliza?tion ability. The method is especially useful in medical diagnostic.
Keywords：cost sensitivemisclassification coststest costswait time costsmulti-objective optimizationdecision tree
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 3020-3024 )