NDLI: The Effect of History on Modeling Systems' Performance: The Problem of the Demanding Lord

Content Provider	IEEE Xplore Digital Library
Author	Giannakopoulos, G. Palpanas, T.
Copyright Year	2010
Abstract	In several concept attainment systems, ranging from recommendation systems to information filtering, a sliding window of learning instances has been used in the learning process to allow the learner to follow concepts that change over time. However, no analytic study has been performed on the relation between the size of the sliding window and the performance of a learning system. In this work, we present such an analytic model that describes the effect of the sliding window size on the prediction performance of a learning system based on iterative feedback. Using a signal-to-noise approach to model the learning ability of the underlying machine learning algorithms, we can provide good estimates of the average performance of a modeling system independently of the supervised machine learning algorithm employed. We experimentally validate the effectiveness of the proposed methodology with detailed experiments using synthetic and real datasets, and a variety of learning algorithms, including Support Vector Machines, Naive Bayes, Nearest Neighbor and Decision Trees. The results validate the analysis and indicate very good estimation performance in different settings.
Starting Page	809
Ending Page	814
File Size	1214407
Page Count	6
File Format	PDF
ISBN	9781424491315
ISSN	15504786
DOI	10.1109/ICDM.2010.90
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-13
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Learning systems Training Noise Correlation Decision trees Machine learning demanding lord problem concept drift user modeling adaptive learning
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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