NDLI: Shapely value based random subspace selection for hyperspectral image classification

Content Provider	IEEE Xplore Digital Library
Author	Gurram, P. Heesung Kwon Davidson, C.
Copyright Year	2015
Description	Author affiliation: Res. Lab., U.S. Army, Adelphi, MD, USA (Gurram, P.; Heesung Kwon) \|\| Sci. & Technol. Corp., Edgewood, MD, USA (Davidson, C.)
Abstract	In this paper, an algorithm to randomly select feature sub-spaces for hyperspectral image classification using the principle of coalition game theory is presented. The feature selection algorithms associated with non-linear kernel based Support Vector Machines (SVM) are either NP-hard or greedy and hence, not very optimal. To deal with this problem, a metric based on the principles of coalition game theory called Shapely value and a sampling approximation is used to determine the contributions of individual features towards the classification task. Feature subsets are randomly drawn from a probability distribution function generated using normalized Shapely values of the individual features. These feature subsets are then used to build kernels corresponding to individual weak classifiers in the Sparse Kernel-based Ensemble Learning (SKEL) framework. By weighting the kernels optimally and sparsely, a small number of useful subsets of features are selected which improve the generalization performance of the ensemble classifier. The algorithm is applied on real hyper-spectral datasets and the results are presented in the paper.
Starting Page	4975
Ending Page	4978
File Size	838401
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7326949
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Support vector machines Hyperspectral imaging Chemicals Game theory Feature extraction
Content Type	Text
Resource Type	Article

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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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