NDLI: Evaluating Threshold for Retraining Rule in Semi-supervised Learning Using Multi-expert System

Content Provider	IEEE Xplore Digital Library
Author	Impedovo, S. Barbuzzi, D. Pirlo, G.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Bari Aldo MORO, Bari, Italy (Impedovo, S.; Barbuzzi, D.; Pirlo, G.)
Abstract	The creation of training set, for pattern recognition, is a difficult, expensive and time consuming task because it requires the efforts of experienced human annotators. On the other hand, unlabeled data can be obtained cheaply, but there are few ways to use them. Semi-Supervised learning uses both labeled and unlabeled data for classification task. In this paper we propose three methods to apply semi-supervised learning to re-train individual classifiers in a multi-expert scenario. More specifically, these methods are focused on a feedback-based process and on the acceptance threshold that defines what data must be selected for feedback. For the experimental results, carried out on the CEDAR (handwritten digits) database, a SVM classifier and two different combination techniques at measurement level have been used. The results show the effectiveness of the proposed approach with respect to Self-Training and Co-Training algorithms.
Starting Page	169
Ending Page	174
File Size	258087
Page Count	6
File Format	PDF
ISBN	9781479943357
ISSN	21676445
e-ISBN	9781479943340
DOI	10.1109/ICFHR.2014.36
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-01
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Erbium Training Knowledge based systems Feeds Semisupervised learning Support vector machines Pattern recognition Handwritten Digit Classification Semi-Supervised Learning Instance Selection Intelligent Multi-Expert System Feedback-based Strategy
Content Type	Text
Resource Type	Article

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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
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