NDLI: Distilling classification models from cross validation runs: an application to mass spectrometry

Content Provider	IEEE Xplore Digital Library
Author	Kalousis, A. Prados, J. Sanchez, J.-C. Allard, L. Hilario, M.
Copyright Year	2004
Description	Author affiliation: CSD, Geneva Univ., Switzerland (Kalousis, A.; Prados, J.)
Abstract	We present work on a proteomics application. More specifically, from the domain of mass-spectrometry and the identification of biomarkers for stroke attacks. Mass-spectrometry based biomarker identification is an application that sets a number of challenges to the knowledge discovery process. We describe how we tackle them and present a number of machine learning experiments that we performed in order to identify the most suitable learning algorithm for the given problem. However working with real world applications one of the main issues apart from good classification performance is an indication of the factors that really determine the classification decision. Usually based on the results of a resampled-based performance estimation, e.g. cross validation, an algorithm is selected that will provide the operational classification model. On a next step the operational model should be constructed, nevertheless it is not obvious how this should be done since in resampled-based procedures a number of different models are created. We propose a method for linear classifiers that examines the different models produced with cross-validation. The method examines the stability of the models produced from the different training folds and combines them to provide a single model.
Sponsorship	IEEE Comput. Soc.
Starting Page	113
Ending Page	119
File Size	135588
Page Count	7
File Format	PDF
ISBN	076952236X
ISSN	10823409
DOI	10.1109/ICTAI.2004.51
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-11-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mass spectroscopy Stability Biomarkers Biological system modeling Machine learning Proteins Proteomics Machine learning algorithms Chemistry Laboratories
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
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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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