{"title":"Uncertain Information Classification: A Four-Way Decision Making Approach","authors":"Pritpal Singh, Kinjal Rabadiya","doi":"10.1109/ICAPR.2017.8593087","DOIUrl":null,"url":null,"abstract":"In this study, the concept of four-way decision space (4WDS) is introduced. In real life, most of the information is incomplete furthermore, uncertain. From such kind of information, it is extremely dreary to take the precise levels of decision. In the proposed concept, such kind of information can easily be classified into the four distinct regions, as: fuzzy positive region, fuzzy negative region, completely fuzzy region and gray fuzzy region. These four regions comprise of four various types of uncertain information. For each particular region, decision rules can be set up from the classified uncertain information. For a better portrayal of this information, a graphical approach is proposed. This study provides a new insight into the uncertain information by classifying and visualizing them using the 4WDS concept and the proposed graphical approach.","PeriodicalId":239965,"journal":{"name":"2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAPR.2017.8593087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this study, the concept of four-way decision space (4WDS) is introduced. In real life, most of the information is incomplete furthermore, uncertain. From such kind of information, it is extremely dreary to take the precise levels of decision. In the proposed concept, such kind of information can easily be classified into the four distinct regions, as: fuzzy positive region, fuzzy negative region, completely fuzzy region and gray fuzzy region. These four regions comprise of four various types of uncertain information. For each particular region, decision rules can be set up from the classified uncertain information. For a better portrayal of this information, a graphical approach is proposed. This study provides a new insight into the uncertain information by classifying and visualizing them using the 4WDS concept and the proposed graphical approach.