{"title":"在接收机工作特性下按面积排序多准则决策方法","authors":"Seyed Behnam Khakbaz, Maryam Karimi Davijani","doi":"10.11648/J.JIM.20150405.21","DOIUrl":null,"url":null,"abstract":"One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome","PeriodicalId":42560,"journal":{"name":"Journal of Investment Management","volume":"4 1","pages":"210"},"PeriodicalIF":0.7000,"publicationDate":"2015-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Ranking Multi Criteria Decision Making Methods for a Problem by Area Under Receiver Operating Characteristic\",\"authors\":\"Seyed Behnam Khakbaz, Maryam Karimi Davijani\",\"doi\":\"10.11648/J.JIM.20150405.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome\",\"PeriodicalId\":42560,\"journal\":{\"name\":\"Journal of Investment Management\",\"volume\":\"4 1\",\"pages\":\"210\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2015-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Investment Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/J.JIM.20150405.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Investment Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.JIM.20150405.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 4
摘要
多准则决策方法的选择是决策过程中面临的主要挑战之一。这些方法不能给决策者提供相同的答案。因此,选择最佳答案是一个重要的难题。为了解决这一问题,人们提出了Borda和Copeland编译等方法。然而,应用这些方法会导致混合解决方案,这并不一定是最好的答案。本文提出了一种对不同MCDM方法进行排序的新方法。该方法称为AUROC (area under receiver operating characteristic),是一种用于分类模型排序的数据挖掘工具。结果表明,在具有历史结果的巨大选择问题中,应用AUROC对MCDM方法进行排序具有很大的潜力
Ranking Multi Criteria Decision Making Methods for a Problem by Area Under Receiver Operating Characteristic
One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome