Principal Component Analysis with K-nn classification is often used in the field of electronic nose. The classification is usually based on consensual vote of the nearest neighbors. In this paper, a different decision policy is implemented, based on an adaptive vote which takes into account the structure of the-knowledge set. The method is tested on an experimental data set acquired with an array of tin oxide sensors for environmental applications.
Improving concentration estimation of pollutant gases by means of K-nn classification with adaptive vote
Roncaglia A;Elmi I;Dori L;
2001
Abstract
Principal Component Analysis with K-nn classification is often used in the field of electronic nose. The classification is usually based on consensual vote of the nearest neighbors. In this paper, a different decision policy is implemented, based on an adaptive vote which takes into account the structure of the-knowledge set. The method is tested on an experimental data set acquired with an array of tin oxide sensors for environmental applications.File in questo prodotto:
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