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<p><b>Abstract</b>—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.</p>
Ensemble classifiers, combining classifiers, nonparametric, nearest-neighbor, interpoint distance, rank statistic, subsample statistic, functional data, artificial nose, electronic nose, analytical chemistry, chemometrics.

C. E. Priebe, "Olfactory Classification via Interpoint Distance Analysis," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 23, no. , pp. 404-413, 2001.
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