Multivariate classification of Southern Brazilian table wines

2020 ◽  
Vol 34 (12) ◽  
Author(s):  
Lucas Hansen ◽  
Marco Flôres Ferrão
Keyword(s):  
Multivariate Classification

Multivariate classification of alcoholics by means of the MMPI.

1969 ◽  
Vol 74 (6) ◽  
pp. 661-669 ◽  
Author(s):  
Steven G. Goldstein ◽  
James D. Linden
Keyword(s):  
Multivariate Classification

scholarly journals High-pass filtering artifacts in multivariate classification of neural time series data

2021 ◽  
Vol 352 ◽  
pp. 109080
Author(s):  
Joram van Driel ◽  
Christian N.L. Olivers ◽  
Johannes J. Fahrenfort
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Multivariate Classification ◽  
High Pass

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods

2017 ◽  
Vol 100 (2) ◽  
pp. 345-350 ◽  
Author(s):  
Ana M Jiménez-Carvelo ◽  
Antonio González-Casado ◽  
Estefanía Pérez-Castaño ◽  
Luis Cuadros-Rodríguez
Keyword(s):  
Olive Oil ◽  
Vegetable Oils ◽  
Edible Oils ◽  
Support Vector ◽  
Classification Methods ◽  
Multivariate Classification ◽  
Chromatographic Fingerprint ◽  
K Nearest Neighbors ◽  
Pls Discriminant Analysis

Abstract A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phaseLC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis tookonly 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil wereused: one input-class, two input-class, and pseudo two input-class.

Multivariate classification of pigments and inks using combined Raman spectroscopy and LIBS

2011 ◽  
Vol 402 (4) ◽  
pp. 1443-1450 ◽  
Author(s):  
Marek Hoehse ◽  
Andrea Paul ◽  
Igor Gornushkin ◽  
Ulrich Panne
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Classification

scholarly journals Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity

2019 ◽  
Vol 45 (4) ◽  
pp. 613-621 ◽  
Author(s):  
Linda A. Antonucci ◽  
Nora Penzel ◽  
Giulio Pergola ◽  
Lana Kambeitz-Ilankovic ◽  
Dominic Dwyer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Attentional Control ◽  
Familial Risk ◽  
Multivariate Classification ◽  
Control Brain ◽  
Brain Functional Connectivity

A single channel sleep-spindle detector based on multivariate classification of EEG epochs: MUSSDET

2018 ◽  
Vol 297 ◽  
pp. 31-43 ◽  
Author(s):  
Daniel Lachner-Piza ◽  
Nino Epitashvili ◽  
Andreas Schulze-Bonhage ◽  
Thomas Stieglitz ◽  
Julia Jacobs ◽  
...  
Keyword(s):  
Single Channel ◽  
Sleep Spindle ◽  
Multivariate Classification
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