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| Carey E. Priebe, "Olfactory Classification via Interpoint Distance Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 4, pp. 404-413, April, 2001. | |||
| BibTex | x | ||
| @article{ 10.1109/34.917575, author = {Carey E. Priebe}, title = {Olfactory Classification via Interpoint Distance Analysis}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {23}, number = {4}, issn = {0162-8828}, year = {2001}, pages = {404-413}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.917575}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Olfactory Classification via Interpoint Distance Analysis IS - 4 SN - 0162-8828 SP404 EP413 EPD - 404-413 A1 - Carey E. Priebe, PY - 2001 KW - Ensemble classifiers KW - combining classifiers KW - nonparametric KW - nearest-neighbor KW - interpoint distance KW - rank statistic KW - subsample statistic KW - functional data KW - artificial nose KW - electronic nose KW - analytical chemistry KW - chemometrics. VL - 23 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—Detection of the presence of a single prespecified chemical analyte at low concentration in complex backgrounds is a difficult application for chemical sensors. This article considers a database of artificial nose observations designed specifically to allow for the investigation of chemical sensor data analysis performance on the problem of trichloroethylene (TCE) detection. We consider an approach to this application which uses an ensemble of subsample classifiers based on interpoint distances. Experimental results are presented indicating that our nonparametric methodology is a useful tool in olfactory classification.
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