Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge …
Partial least squares-discriminant analysis (PLS-DA) is a versatile algorithm that can be
used for predictive and descriptive modelling as well as for discriminative variable selection …
used for predictive and descriptive modelling as well as for discriminative variable selection …
Tutorial: multivariate classification for vibrational spectroscopy in biological samples
Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman
spectroscopy, have been successful methods for studying the interaction of light with …
spectroscopy, have been successful methods for studying the interaction of light with …
Proximal colon–derived O-glycosylated mucus encapsulates and modulates the microbiota
Colon mucus segregates the intestinal microbiota from host tissues, but how it organizes to
function throughout the colon is unclear. In mice, we found that colon mucus consists of two …
function throughout the colon is unclear. In mice, we found that colon mucus consists of two …
A tutorial review: Metabolomics and partial least squares-discriminant analysis–a marriage of convenience or a shotgun wedding
The predominance of partial least squares-discriminant analysis (PLS-DA) used to analyze
metabolomics datasets (indeed, it is the most well-known tool to perform classification and …
metabolomics datasets (indeed, it is the most well-known tool to perform classification and …
Correlation and association analyses in microbiome study integrating multiomics in health and disease
Y Xia - Progress in molecular biology and translational …, 2020 - Elsevier
Correlation and association analyses are one of the most widely used statistical methods in
research fields, including microbiome and integrative multiomics studies. Correlation and …
research fields, including microbiome and integrative multiomics studies. Correlation and …
Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity–A review
AM Jiménez-Carvelo, A González-Casado… - Food research …, 2019 - Elsevier
In recent years, the variety and volume of data acquired by modern analytical instruments in
order to conduct a better authentication of food has dramatically increased. Several pattern …
order to conduct a better authentication of food has dramatically increased. Several pattern …
Disentangling metabolic functions of bacteria in the honey bee gut
It is presently unclear how much individual community members contribute to the overall
metabolic output of a gut microbiota. To address this question, we used the honey bee …
metabolic output of a gut microbiota. To address this question, we used the honey bee …
So you think you can PLS-DA?
Abstract Background Partial Least-Squares Discriminant Analysis (PLS-DA) is a popular
machine learning tool that is gaining increasing attention as a useful feature selector and …
machine learning tool that is gaining increasing attention as a useful feature selector and …
[HTML][HTML] A critical review of recent trends in sample classification using Laser-Induced Breakdown Spectroscopy (LIBS)
L Brunnbauer, Z Gajarska, H Lohninger… - TrAC Trends in Analytical …, 2023 - Elsevier
LIBS-based classification has experienced an ever-increasing interest in the last few years.
LIBS is a well-suited technique for classification tasks based on elemental fingerprinting …
LIBS is a well-suited technique for classification tasks based on elemental fingerprinting …
PCA as a practical indicator of OPLS-DA model reliability
Background: Principal Component Analysis (PCA) and Orthogonal Projections to Latent
Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that …
Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that …