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Comparison of the Performance of Different Discriminant Algorithms in Analyte Discrimination Tasks Using an Array of Carbon Black−Polymer Composite Vapor Detectors

Vaid, Thomas P. and Burl, Michael C. and Lewis, Nathan S. (2001) Comparison of the Performance of Different Discriminant Algorithms in Analyte Discrimination Tasks Using an Array of Carbon Black−Polymer Composite Vapor Detectors. Analytical Chemistry, 73 (2). pp. 321-331. ISSN 0003-2700. https://resolver.caltech.edu/CaltechAUTHORS:20160803-110835979

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Abstract

An array of 20 compositionally different carbon black−polymer composite chemiresistor vapor detectors was challenged under laboratory conditions to discriminate between a pair of extremely similar pure analytes (H_(2)O and D_(2)O), compositionally similar mixtures of pairs of compounds, and low concentrations of vapors of similar chemicals. Several discriminant algorithms were utilized, including k nearest neighbors (kNN, with k = 1), linear discriminant analysis (LDA, or Fisher's linear discriminant), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA, a hybrid of LDA and QDA), partial least squares, and soft independent modeling of class analogy (SIMCA). H_(2)O and D_(2)O were perfectly classified by most of the discriminants when a separate training and test set was used. As expected, discrimination performance decreased as the analyte concentration decreased, and performance decreased as the composition of the analyte mixtures became more similar. RDA was the overall best-performing discriminant, and LDA was the best-performing discriminant that did not require several cross-validations for optimization.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1021/ac000792fDOIArticle
http://pubs.acs.org/doi/abs/10.1021/ac000792fPublisherArticle
ORCID:
AuthorORCID
Lewis, Nathan S.0000-0001-5245-0538
Additional Information:© 2001 American Chemical Society. Received 10 July 2000; accepted 5 October 2000; published online 15 December 2000; published in print 15 January 2001. We acknowledge DARPA, the Army Research Office through a MURI grant, the Department of Energy, and NASA for support of this work.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
Army Research Office (ARO)UNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
NASAUNSPECIFIED
Issue or Number:2
Record Number:CaltechAUTHORS:20160803-110835979
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20160803-110835979
Official Citation:Vaid, T. P., Burl, M. C., & Lewis, N. S. (2001). Comparison of the Performance of Different Discriminant Algorithms in Analyte Discrimination Tasks Using an Array of Carbon Black−Polymer Composite Vapor Detectors. Analytical Chemistry, 73(2), 321-331. doi:10.1021/ac000792f
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69409
Collection:CaltechAUTHORS
Deposited By: Melissa Ray
Deposited On:03 Aug 2016 23:45
Last Modified:03 Oct 2019 10:21

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