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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Characterization and classification of PGI Moroccan Argan oils based on their FTIR fingerprints and chemical composition
Mourad Kharbach,Mourad Kharbach,Rabie Kamal,Mohammed Bousrabat,Mohammed Alaoui Mansouri,Issam Barra,Katim Alaoui,Yahia Cherrah,Yvan Vander Heyden,Abdelaziz Bouklouze +9 more
TL;DR: In this paper, Fourier Transform Infrared Spectroscopy (FTIR) was selected as a reliable, fast and non-destructive technique to record spectroscopic fingerprints of Moroccan Protected Geographical Indication (PGI) Argan oils.
Journal ArticleDOI
Recent trends in application of chemometric methods for GC-MS and GC×GC-MS-based metabolomic studies
TL;DR: In this paper, a review of different methods used for processing of metabolomics data generated from gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional GC-MS is presented.
Journal ArticleDOI
Evaluation of attached mortar on recycled concrete aggregates by hyperspectral imaging
TL;DR: In this paper, an innovative sensor-based quality control strategy was developed using hyperspectral imaging (HSI) in the near-infrared range (1000-1700nm), to evaluate the residual mortar content on the surface of coarse recycled concrete aggregates.
Journal ArticleDOI
Development and Validation of a Near-Infrared Spectroscopy Method for the Prediction of Acrylamide Content in French-Fried Potato
TL;DR: NIRS can be used as a screening tool in potato breeding and potato processing research to reduce acrylamide in the food supply, and the findings indicate that NIRS could accurately detect acryamide content as low as 50 μg/kg in the model potato matrix.
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Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods.
TL;DR: F Fourier transform Mid-infrared spectroscopy was used in the present work as a fingerprinting technique to detect the presence of three adulterants (soybean, maize and wheat flours), and partial least squares discriminant analysis (PLS-DA) showed better classification results than SIMCA.
References
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Journal ArticleDOI
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.