Show simple item record Rasmani, Khairul Shen, Qiang 2008-01-15T21:09:37Z 2008-01-15T21:09:37Z 2005
dc.identifier.citation Rasmani , K & Shen , Q 2005 , ' Subsethood-based Fuzzy Rule Models and their Application to Student Performance ' pp. 755-760 . en
dc.identifier.other PURE: 74588
dc.identifier.other PURE UUID: b359934c-84d7-4ed5-b0fb-b0c29b919e66
dc.identifier.other dspace: 2160/433
dc.identifier.other DSpace_20121128.csv: row: 332
dc.identifier.other Scopus: 23944491439
dc.identifier.uri en
dc.description K. Rasmani and Q. Shen. Subsethood-based Fuzzy Rule Models and their Application to Student Performance Classification. Proceedings of the 14th International Conference on Fuzzy Systems, pages 755-760, 2005. en
dc.description.abstract The focus of this paper is the use of fuzzy approaches to classify student academic performance, which so far has not been performed satisfactorily by existing fuzzy techniques. Instead of using methods that solely rely on expert opinions, student performance evaluation is herein conducted using fuzzy rule-based models which combine expert knowledge with knowledge extracted from data. Significant advantages of the present work are shown by comparing the results obtained with various alternative techniques. In addition to the ability to produce classification that helps the students to understand their performance, the use of membership value degrees in both rule antecedents and conclusions allows one to confirm or refute results in certain borderline cases that were obtained by other means (e.g. by a human evaluator). In particular, this advantage is coupled with a simpler modelling mechanism that minimizes human intervention by avoiding the use of preset threshold values which are typically used in conventional subsethood based models. en
dc.format.extent 6 en
dc.language.iso eng
dc.relation.ispartof en
dc.rights en
dc.title Subsethood-based Fuzzy Rule Models and their Application to Student Performance en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontoconference/paper en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Non peer reviewed en

Files in this item

Aside from theses and in the absence of a specific licence document on an item page, all works in Cadair are accessible under the CC BY-NC-ND Licence. AU theses and dissertations held on Cadair are made available for the purposes of private study and non-commercial research and brief extracts may be reproduced under fair dealing for the purpose of criticism or review. If you have any queries in relation to the re-use of material on Cadair, contact

This item appears in the following Collection(s)

Show simple item record

Search Cadair

Advanced Search