中文摘要：

随着数据挖掘和机器学习技术在实际问题中的广泛应用,人们越来越多的发现实际分类问题通常具有代价敏感特性.代价敏感的分类是指在同一分类任务中错误分类的代价是不同的.介绍了一种基于构造性覆盖算法的代价敏感三支决策模型,即将代价敏感引入到基于构造性覆盖算法的三支决策模型.该模型根据误分类之间的大小关系来减少正、负覆盖的个数,从而调整三个域,即正域、负域和边界域的大小.引入代价敏感的目的是尽可能的减少划分损失.实验对比了本文的模型分类结果和基于决策粗糙集的三支决策模型,结果表明,本文的模型分类结果稳定,并且能够通过改变三个域的大小,把分类损失最小化.

英文摘要：

As data mining and machine learning techniques are widely used in practical problems,we find that more and more actual classification problems typically have cost-sensitive characteristics.The cost-sensitive classification refers to the cost of classification which is different in the same category classification task.This paper introduces a cost-sensitive three-way decisions model based on Constructive Covering Algorithm,i.e.,which connects the characteristics cost-sensitive with three-way decisions model based on Constructive Covering Algorithm.This new model reduces the number of covers and modifies the three regions according to the loss functions.The three regions are positive region,negative region and boundary region,respectively.The purpose to introduce cost-sensitive is to reduce the division cost as far as possible.Experiments compare the new model which is cost-sensitive three-way decision model based on Constructive Covering Algorithm with three-decision model based on rough set of decisions.The experimental results show that the classification performance of proposed model is stable and the new model can minimize the classification cost according to modify the size of three regions.