Archit Gupta, Sanjiban Sekhar Roy, Sanchit Sabharwal, Rajat Gupta
{"title":"Investigating the factors responsible for hepatitis disease using rough set theory","authors":"Archit Gupta, Sanjiban Sekhar Roy, Sanchit Sabharwal, Rajat Gupta","doi":"10.1109/ICCCNT.2013.6850237","DOIUrl":null,"url":null,"abstract":"The last decade has witnessed a prompt progression in the field of rough set notion. It has been fruitfully applied to numerous diverse fields such as data mining and network intrusion discovery with little or no alterations. A rapid advance of interest in rough set theory and its applications can be recently seen in the number of international workshops, conferences and seminars that are either directly devoted to rough sets or contain the subject in their programs. This paper familiarizes rudimentary notions of rough set theory and then applies them on a data set of hepatitis disease. Major factors responsible for the disease are studied and then we eliminated the surplus data from the information table. Based on the conditions the actions to be taken are defined in the decision algorithms.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"63 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6850237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The last decade has witnessed a prompt progression in the field of rough set notion. It has been fruitfully applied to numerous diverse fields such as data mining and network intrusion discovery with little or no alterations. A rapid advance of interest in rough set theory and its applications can be recently seen in the number of international workshops, conferences and seminars that are either directly devoted to rough sets or contain the subject in their programs. This paper familiarizes rudimentary notions of rough set theory and then applies them on a data set of hepatitis disease. Major factors responsible for the disease are studied and then we eliminated the surplus data from the information table. Based on the conditions the actions to be taken are defined in the decision algorithms.