NDLI: Complementary classifier design using difference principal components

Content Provider	IEEE Xplore Digital Library
Author	Kawatani, T. Shimizu, H.
Copyright Year	1997
Description	Author affiliation: Hewlett-Packard Labs., Kanagawa, Japan (Kawatani, T.)
Abstract	In classifier combination, the degree of recognition accuracy improvement depends not only on how to combine classifiers, but also on how much classifiers complement each other. In order to improve accuracy, therefore, it is important to design complementary classifiers with respect to each other. The authors propose a method to design a classifier complementary to an existent one, which satisfies the requirements: (a) it can recognize patterns misrecognized by the existent classifier with high accuracy, and (b) the number of patterns which are correctly recognized by the existent classifier but turn out to be misrecognized after combination can be minimized. In the proposed method, features are obtained by projection of original features onto axes such that the scatter of projection of patterns of a given class is small and that the squared mean of projection of patterns misrecognized in the given class is large. As the discriminant function, Fisher's linear discriminant function is applied using not only linear terms but also quadratic terms. Through experiments using handwritten numeral data included in the NIST database, it has been confirmed that the requirements mentioned above are satisfied. The misrecognition rate reduce to 56% for training data and to 86% for test data.
Starting Page	875
Ending Page	880
File Size	647497
Page Count	6
File Format	PDF
ISBN	0818678984
DOI	10.1109/ICDAR.1997.620637
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-08-18
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pattern recognition Linear discriminant analysis Design methodology Decision making Laboratories Scattering NIST Databases Training data Testing
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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