NDLI: A comparison for handling imbalanced datasets

Content Provider	IEEE Xplore Digital Library
Author	Syaripudin, A. Khodra, M.L.
Copyright Year	2014
Description	Author affiliation: Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandungw Bandung, Bandung, Indonesia (Syaripudin, A.; Khodra, M.L.)
Abstract	In various real case, imbalanced datasets problems are inevitable, such as in metal detecting security or diagnosis of disease. With the limitations of existing learning algorithms when faced with imbalanced datasets, the prediction error is caused by the dominance of the majority against the minority class. Various techniques have been made to address the above circumstances. This paper compares those techniques of handling imbalanced datasets with resample and ensembles. From a different standpoint, this paper examines how much influence the number of instances, number of attributes, the attributes data types, the number of the target class, and missing attribute values affect the classification results with performance analysis using f-measure. An experiment has resulted that the criteria regarding the number of attributes, attribute data types, and the number of the target class do not affect the classification results. While the missing attribute with values have an affect classification result. For better high F-measure, the experiment shows that the best performer is combination of SMOTE 5000/0 and AdaBoostMl.
Starting Page	293
Ending Page	298
File Size	337689
Page Count	6
File Format	PDF
ISBN	9781479969845
e-ISBN	9781479951000
DOI	10.1109/ICAICTA.2014.7005957
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-20
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Training Imbalanced dataset Error analysis Conferences Nickel Informatics Ensembles Resamples
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
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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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