NDLI: Extending extension theory for classifying data with numerical values

Content Provider	Springer Nature Link
Author	Liu, Cheng Hsiang
Copyright Year	2012
Abstract	The extension theory (ET) is one of the simplest and most attractive pattern classification methods. However, it has difficulty determining the classical domain. In addition, the traditional extended relational function used in extension theory does not provide very useful summaries of asymmetrical data. This study proposes a modified extension theory (MET) to overcome these shortcomings. The MET applies the largest sphere concept to determine the range of the classical domains and incorporates the information about the data distribution when calculating the relevance of an element belonging to a set. Experimental results indicate that the MET consistently achieved better or comparable results than the traditional ET. The MET also produces a classifier with satisfactory classification accuracy compared with well-known classifiers (e.g., decision trees and k-nearest neighbor).
Starting Page	161
Ending Page	167
Page Count	7
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	23
Issue Number	1
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-01-08
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Extension theory Classical domain Classification Numerical data set Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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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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