Journal ArticleDOI
Classification tools in chemistry. Part 1: linear models. PLS-DA
Davide Ballabio,Viviana Consonni +1 more
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TLDR
The common steps to calibrate and validate classification models based on partial least squares discriminant analysis are discussed in the present tutorial, and issues to be evaluated during model training and validation are introduced and explained using a chemical dataset.Abstract:
The common steps to calibrate and validate classification models based on partial least squares discriminant analysis are discussed in the present tutorial. All issues to be evaluated during model training and validation are introduced and explained using a chemical dataset, composed of toxic and non-toxic sediment samples. The analysis was carried out with MATLAB routines, which are available in the ESI of this tutorial, together with the dataset and a detailed list of all MATLAB instructions used for the analysis.read more
Citations
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Combination of excitation-emission matrix fluorescence spectroscopy and chemometric methods for the rapid identification of cheaper vegetable oil adulterated in walnut oil
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Traceability of soybeans produced in Argentina based on their trace element profiles
Melisa Jazmin Hidalgo,Diana Corina Fechner,Davide Ballabio,Eduardo Jorge Marchevsky,Roberto Gerardo Pellerano +4 more
TL;DR: Multielement analysis of soybean grains samples in combination with chemometric tools was used to classify the geographical origins of samples from Argentina, suggesting that the developed methodology by chemometric techniques is robust and reliable.
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Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics
TL;DR: In this article, an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu.
Journal ArticleDOI
Elevated Gamma Connectivity in Nidopallium Caudolaterale of Pigeons during Spatial Path Adjustment
TL;DR: This study examined neural activity in the NCL of pigeons and explored the local field potentials’ spectral and functional connectivity patterns in a goal-directed spatial cognitive task with the detour paradigm, finding the pigeons progressively learned to solve the path adjustment task when the learned path was blocked suddenly.
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Detection of Soybean Powder and Rice Flour Adulterations in Premature Formula by ATR-FTIR Spectroscopy and Chemometrics
TL;DR: In this paper, the authors implemented the combinatorial method of Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with chemometrics to identify and classify PIFP samples contaminated with Rice flour (RF) and soybean powder (SP).
References
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Beware of q2
TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.
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Computer Aided Design of Experiments
Robert W. Kennard,L. A. Stone +1 more
TL;DR: A computer oriented method which assists in the construction of response surface type experimental plans takes into account constraints met in practice that standard procedures do not consider explicitly.
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PLS regression methods
TL;DR: In this paper, the mathematical and statistical structure of PLS regression is developed and the PLS decomposition of the data matrices involved in model building is analyzed. But the PLP regression algorithm can be interpreted in a model building setting.
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Kohonen and counterpropagation artificial neural networks in analytical chemistry
TL;DR: The principles of the Kohonen and counterpropagation artificial neural network (K-ANN and CP-ANN) learning strategy is described and the use of both methods is explained with several examples from analytical chemistry.
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Calculation of the reliability of classification in discriminant partial least-squares binary classification
TL;DR: This method, called Probabilistic Discriminant Partial Least Squares (p-DPLS), integrates DPLS, density methods and Bayes decision theory in order to take into account the uncertainty of the predictions in DPLs.