Analytical Methods· 2013Q2
Classification tools in chemistry. Part 1: linear models. PLS-DA
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- Q2SCImago
- 2013year
Short summary
This tutorial explains the calibration and validation steps for classification models using Partial Least Squares Discriminant Analysis (PLS-DA) in chemistry.
AI-generated from the title and abstract; the full text is not read.
Key points
- Discusses calibration and validation for PLS-DA classification models.
- Explains issues evaluated during model training and validation.
- Uses a chemical dataset of toxic and non-toxic sediment samples for illustration.
- Provides MATLAB routines, dataset, and instructions for reproducibility.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Analytical Methods, 2013 · DOI ↗
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Field: Analytical Chemistry
Analytical ChemistryChemistry