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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Detecting compositional changes in dielectric materials simulated by three-dimensional RC network models
TL;DR: In this article, a principal component analysis (PCA) method is employed to discriminate normal samples from samples with altered composition on the basis of statistics extracted from the waveform of the network response to a given excitation.
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In vivo non-invasive near-infrared spectroscopy distinguishes normal, post-stroke, and botulinum toxin treated human muscles.
Antonio Currà,Riccardo Gasbarrone,Alessandra Cardillo,Francesco Fattapposta,Paolo Missori,Lucio Marinelli,Giuseppe Bonifazi,Silvia Serranti,Carlo Trompetto +8 more
TL;DR: In this article, the spectral fingerprints of the elbow flexors and extensors were collected using VIS and short-wave infrared (SWIR) reflectance spectra in vivo using a portable spectroradiometer (350-2500nm).
Journal ArticleDOI
Application of classification models to identify solvents for single-walled carbon nanotubes dispersion
TL;DR: In this paper, a list of classification models was developed to categorise organic solvents with respect to their dispersibility of single-walled carbon nanotubes (SWNTs).
Non linear classification of commercial mexican tequilas
TL;DR: PLS‐DA was found to behave poorly when 3 classes of tequilas were modeled to study a collection of 170 commercial Mexican spirits measured by UV‐Vis spectroscopy, and QDA was selected for routine assessments thanks to its simplicity and broad availability.
Journal ArticleDOI
The Use of Gas Chromatography Coupled with High-Resolution Mass Spectrometry-Based Untargeted Metabolomics to Discover Metabolic Changes and Help in the Determination of Complex Causes of Death: A Preliminary Study
TL;DR: In this article, gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS)-based untargeted metabolomics was employed to obtain plasma metabolic profiles of rats that died from anaphylactic shock (AS), mechanical asphyxia (MA), or sudden cardiac death (SCD).
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.