NDLI: Effective Classification Using a Small Training Set Based on Discretization and Statistical Analysis

Content Provider	IEEE Xplore Digital Library
Author	Bruni, R. Bianchi, G.
Copyright Year	1989
Abstract	This work deals with the problem of producing a fast and accurate data classification, learning it from a possibly small set of records that are already classified. The proposed approach is based on the framework of the so-called Logical Analysis of Data (LAD), but enriched with information obtained from statistical considerations on the data. A number of discrete optimization problems are solved in the different steps of the procedure, but their computational demand can be controlled. The accuracy of the proposed approach is compared to that of the standard LAD algorithm, of support vector machines and of label propagation algorithm on publicly available datasets of the UCI repository. Encouraging results are obtained and discussed.
Sponsorship	IEEE IEEE Comput. Soc. Tech. Committee on Data Eng IEEE Computer Society
Starting Page	2349
Ending Page	2361
Page Count	13
File Size	419498
File Format	PDF
ISSN	10414347
Volume Number	27
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Support vector machines Accuracy Standards Machine learning algorithms Prediction algorithms Decision trees Optimization Classification Algorithms Data Mining Machine Learning Discrete Mathematics optimization Classification algorithms data mining machine learning discrete mathematics
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Computational Theory and Mathematics Information Systems

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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	Mr. Siddhartha Mukherjee siddhartha@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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