基于三支决策模型的代价敏感数据分类方法
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摘要
三支决策是近年来提出的一种新的决策理论模型,为了将该模型应用于数据的分类中,提出一种基于三支决策的代价敏感数据分类方法。首先根据三支决策模型,定义一种新形式的误分类代价,并提出相应的最小化误分类代价特征选择算法,然后在该特征选择算法的基础上,提出三支决策模型的代价敏感数据分类算法,该算法将数据分类结果分成三种情形,分别为标记特定类别、不标记特定类别和暂不标记。最后通过仿真实验证明了文中所提出的算法具有更好的代价敏感分类效果。
The three-way decision is a new decision theory model proposed in recent years. In order to apply the decision model to data classification,a cost sensitive data classification method based on three-way decisions was proposed. Firstly,a new form of misclassification cost was defined based on the three-way decision model,and a corresponding minimized misclassification cost feature selection algorithm was proposed. Then,on the basis of the feature selection algorithm,a cost sensitive data classification algorithm for three-way decision models was proposed. This algorithm divided the data classification results into three categories,namely,marking specific categories,not marking specific categories and temporarily unmarked. Finally,simulation experiment results show that the proposed algorithm has better cost sensitive classification effect.
The three-way decision is a new decision theory model proposed in recent years. In order to apply the decision model to data classification,a cost sensitive data classification method based on three-way decisions was proposed. Firstly,a new form of misclassification cost was defined based on the three-way decision model,and a corresponding minimized misclassification cost feature selection algorithm was proposed. Then,on the basis of the feature selection algorithm,a cost sensitive data classification algorithm for three-way decision models was proposed. This algorithm divided the data classification results into three categories,namely,marking specific categories,not marking specific categories and temporarily unmarked. Finally,simulation experiment results show that the proposed algorithm has better cost sensitive classification effect.
引文
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[15]TANG Z M,LIAO W H,JIA X Y,et al.Minimum cost attribute reduction in decision-theoretic rough set models[J].Information Sciences,2013,219(01):151-167.
[16]LI W W,HUANG Z Q,JIA X Y,et al.Neighborhood based decision-theoretic rough set models[J].International Journal of Approximate Reasoning,2016,69(c):1-17.
[17]徐波,张贤勇,冯山.邻域粗糙集的加权依赖度及其启发式约简算法[J].模式识别与人工智能,2018,31(03):256-264.
[2]YAO Y Y.The superiority of three-way decisions in probabilistic rough set models[J].Information Sciences,2011,181(06):1080-1096.
[3]SUN B Z,MA W M,XIAO X.Three-way group decision making based on multigranulation fuzzy decisiontheoretic rough set over two universes[J].International Journal of Approximate Reasoning,2017,81:87-102.
[4]XU J F,MIAO D Q,ZHANG Y J,et al.A three-way decisions model with probabilistic rough sets for stream computing[J].International Journal of Approximate Reasoning,2017,88:1-22.
[5]YU H,LIU Z G,WANG G Y.An automatic method to determine the number of clusters using decisiontheoretic rough set[J].International Journal of Approximate Reasoning,2014,55(01):101-115.
[6]YU H,WANG X,WANG G Y,et al.An active three-way clustering method via low-rank matrices for multi-view data[J].Information Sciences,2018.
[7]ZHANG H R,MIN F.Three-way recommender systems based on random forests[J].Knowledge-Based Systems,2016,91:275-286.
[8]NAUMAN M,AZAM N,YAO J T.A three-way decision making approach to malware analysis using probabilistic rough sets[J].Information Sciences,2016,374(20):193-209.
[9]谢骋,商琳.基于三支决策粗糙集的视频异常行为检测[J].南京大学学报(自然科学版),2013,49(04):475-482.
[10]ZHOU B,YAO Y,LUO J.Cost-sensitive three-way email spam filtering[J].Journal of Intelligent Information Systems,2014,42(01):19-45.
[11]李建林,黄顺亮.多阶段三支决策垃圾短信过滤模型[J].计算机科学与探索,2014,8(02):226-233.
[12]张越兵,苗夺谦,张志飞.基于三支决策的多粒度文本情感分类模型[J].计算机科学,2017,44(12):188-193.
[13]贾永强,甘露.基于特征降维的卫星通信辐射源个体识别方法[J].测控技术,2017,36(11):14-17.
[14]SONG J J,TSANG ECC,CHEN D G,et al.Minimal decision cost reduct in fuzzy decision-theoretic rough set model[J].Knowledge-Based Systems,2017,126(c):104-112.
[15]TANG Z M,LIAO W H,JIA X Y,et al.Minimum cost attribute reduction in decision-theoretic rough set models[J].Information Sciences,2013,219(01):151-167.
[16]LI W W,HUANG Z Q,JIA X Y,et al.Neighborhood based decision-theoretic rough set models[J].International Journal of Approximate Reasoning,2016,69(c):1-17.
[17]徐波,张贤勇,冯山.邻域粗糙集的加权依赖度及其启发式约简算法[J].模式识别与人工智能,2018,31(03):256-264.