NDLI: Feature selection with mutual information for regression problems

Content Provider	IEEE Xplore Digital Library
Author	Sulaiman, M.A. Labadin, J.
Copyright Year	2015
Description	Author affiliation: Fac. of Comput. Sci. & Inf. Technol., Univ. Malaysia Sarawak, Kota Samarahan, Malaysia (Sulaiman, M.A.; Labadin, J.)
Abstract	selecting relevant features for machine learning modeling improves the performance of the learning methods. Mutual information (MI) is known to be used as relevant criterion for selecting feature subsets from input dataset with a nonlinear relationship to the predicting attribute. However, mutual information estimator suffers the following limitation; it depends on smoothing parameters, the feature selection greedy methods lack theoretically justified stopping criteria and in theory it can be used for both classification and regression problems, however in practice more often it formulation is limited to classification problems. This paper investigates a proposed improvement on the three limitations of the Mutual Information estimator (as mentioned above), through the use of resampling techniques and formulation of mutual information based on differential entropic for regression problems.
Starting Page	1
Ending Page	6
File Size	398718
Page Count	6
File Format	PDF
e-ISBN	9781479999392
DOI	10.1109/CITA.2015.7349826
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-04
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature Selection Uncertainty Smoothing methods Computational modeling Regression Problems Mutual Information Entropy Yttrium Mathematical model Mutual information
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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