NDLI: A systematic and reliable approach to pattern classification

Content Provider	IEEE Xplore Digital Library
Author	Doraiswami, R. Stevenson, M. Rajan, S.
Copyright Year	1999
Description	Author affiliation: New Brunswick Univ., Fredericton, NB, Canada (Doraiswami, R.)
Abstract	A systematic and reliable approach to classify patterns is proposed when no a priori information except a set of pre-classified data is provided. A classifier is selected from a number of state of the art pattern classification schemes which are diverse in approach as well as the assumptions employed in their design. The selected schemes include the k-nearest neighbour classifier (kNNC), the minimum Mahalanobis distance classifier (MMDC), and the artificial neural network classifier (ANNC). In order to ensure that the selected classification scheme is properly designed and correctly implemented, the given pre-classified data is analysed, and the relative performance of the classifiers are cross validated as well as compared with a benchmark performance measure. The given data set is subjected to data validation, data visualization and feature quality analysis with a view to detect bad data, to obtain a qualitative picture of the class separability, and to derive a benchmark performance measure called the Bhattacharyya distance measure. In the design phase, the classifiers are executed in the order of increasing accuracy and increasing complexity so that a classifier at one level in the hierarchy sets the performance goal (e.g. classification accuracy) for the task at the next level. Further, to ensure a peak performance, the classifier accuracy is compared with the Bhattacharyya distance measure. The proposed scheme is evaluated on both simulated as well as actual data obtained from the images of the biological cells.
Starting Page	735
Ending Page	741
File Size	462156
Page Count	7
File Format	PDF
ISBN	0780354893
DOI	10.1109/IPMM.1999.791479
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fourier transforms Data analysis Biological system modeling Medical simulation Discrete Fourier transforms Pattern classification Artificial neural networks Discrete wavelet transforms Performance analysis Niobium
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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