NDLI: Mining quantitative class-association rules for software size estimation

Content Provider	IEEE Xplore Digital Library
Author	Moreno, M.N. Lucas, J.P. Segrera, S. Lopez, V.F.
Copyright Year	2009
Description	Author affiliation: Department of Computing and Automatic, University of Salamanca, Salamanca, Spain (Moreno, M.N.; Lucas, J.P.; Segrera, S.; Lopez, V.F.)
Abstract	Associative models are usually applied in knowledge discovery problems in order to find patterns in large databases containing mainly nominal data. This work is focused on two different aspects, the predictive use of association rules and the management of quantitative attributes. The aim is to induce class association rules that allow predicting software size from attributes obtained in early stages of the project. In this application area, most of the attributes are continuous; therefore, they should be discretized before generating the rules. Discretization is a data mining preprocessing task having a special importance in association rule mining since it has a significant influence on the quality and the predictive precision of the induced rules. In this paper, a multivariate supervised discretization method is proposed, which takes into account the predictive purpose of the association rules.
Starting Page	199
Ending Page	204
File Size	258558
Page Count	6
File Format	PDF
ISBN	9781424450213
DOI	10.1109/ISCIS.2009.5291844
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-14
Publisher Place	Cyprus
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Associative classification Costs Induction generators Decision making Project management class association rules Predictive models Association rules Data mining Application software Databases Supervised learning discretization software size estimation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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