NDLI: Ambiguity-Based Multiclass Active Learning

Content Provider	IEEE Xplore Digital Library
Author	Ran Wang Chi-Yin Chow Sam Kwong
Copyright Year	1993
Abstract	Most existing works on active learning (AL) focus on binary classification problems, which limit their applications in various real-world scenarios. One solution to multiclass AL (MAL) is evaluating the informativeness of unlabeled samples by an uncertainty model and selecting the most uncertain one for query. In this paper, an ambiguity-based strategy is proposed to tackle this problem by applying a possibility approach. First, the possibilistic memberships of unlabeled samples in the multiple classes are calculated from the one-against-all-based support vector machine model. Then, by employing fuzzy logic operators, these memberships are aggregated into a new concept named k-order ambiguity, which estimates the risk of labeling a sample among k classes. Afterward, the k-order ambiguities are used to form an overall ambiguity measure to evaluate the uncertainty of the unlabeled samples. Finally, the sample with the maximum ambiguity is selected for query, and a new MAL strategy is developed. Experiments demonstrate the feasibility and effectiveness of the proposed method.
Sponsorship	IEEE Computational Intelligence Society
Starting Page	242
Ending Page	248
Page Count	7
File Size	1277180
File Format	PDF
ISSN	10636706
Volume Number	24
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Training Standards Uncertainty Entropy Complexity theory Fuzzy logic Fuzzy sets and fuzzy logic Active learning ambiguity possibility approach Active learning (AL) fuzzy sets and fuzzy logic multiclass
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Control and Systems Engineering Computational Theory and Mathematics

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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