NDLI: Bagging based ensemble transfer learning

Content Provider	Springer Nature Link
Author	Liu, Xiaobo Wang, Guangjun Cai, Zhihua Zhang, Harry
Copyright Year	2015
Abstract	Nowadays, transfer learning is one of the main research areas in machine learning that is helpful for labeling the data with low cost. In this paper, we propose a novel bagging-based ensemble transfer learning (BETL). The BETL framework includes three operations: Initiate, Update, and Integrate. In the Initiate operation, we use bootstrap sampling to divide the source data into many subsets, and add the labeled data from the target domain into these subsets separately so that the source data and the target data arrive at a reasonable ratio, then we learn as many initial classifiers as the elements of an ensemble. In the Update operation, we utilize the initial classifiers and an updateable classifier to repeatedly label the data that hasn’t been labeled yet in the target domain, and then, add the newly labeled data into the target domain to renew the updateable classifier. In the Integrate operation, we integrate the updated classifiers from each iteration into a pool to predict the labels of the test data via the majority vote strategy. In order to demonstrate the effectiveness of our method in the classification process, we conduct experiments on UCI data set, real world data set, and text data set. The results show that our method can effectively label the unlabeled data in the target domain, which greatly enhances the performance of target domain.
Starting Page	29
Ending Page	36
Page Count	8
File Format	PDF
ISSN	18685137
Journal	Journal of Ambient Intelligence and Humanized Computing
Volume Number	7
Issue Number	1
e-ISSN	18685145
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-06-24
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bagging Ensemble method Transfer learning Machine learning Computational Intelligence Artificial Intelligence (incl. Robotics) Robotics and Automation User Interfaces and Human Computer Interaction
Content Type	Text
Resource Type	Article
Subject	Computer Science

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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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