Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination. AbstractThis study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine’s quality in each individual cluster was carried out according to individual laboratory parameters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Scientifica Naturalis de Gruyter

Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

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Publisher
de Gruyter
Copyright
© 2018 I. P. Bangov et al., published by De Gruyter Open
eISSN
2367-5144
D.O.I.
10.2478/asn-2018-0004
Publisher site
See Article on Publisher Site

Abstract

AbstractThis study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine’s quality in each individual cluster was carried out according to individual laboratory parameters.

Journal

Acta Scientifica Naturalisde Gruyter

Published: Mar 1, 2018

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