Partial Least Squares (PLS) is a wide class of methods for modeling relations between sets of observed variables by means of latent variables. It comprises of regression and classification tasks as well as dimension reduction techniques and modeling tools. The underlying assumption of all PLS methods is that the observed data is generated by a system or process which is driven by a small number...

BACKGROUND The methicillin-resistant Staphylococcus aureus (MRSA) surface protein Pls (plasmin sensitive) reduces adhesion to host proteins and cellular invasiveness by an unknown mechanism that requires Pls expression. Here, we tested the effect of Pls expression using different pls-negative backgrounds. METHODS Three pls-negative strains (the methicillin-susceptible Staphylococcus aureus st...

Visible and near-infrared (Vis-NIR) diffuse reflectance spectroscopy with partial least squares (PLS) regression is a quick, cost-effective, and promising technology for predicting soil properties. The advantage of PLS regression is that all available wavebands can be incorporated in the model, while earlier studies indicate that PLS models include redundant wavelengths, and selecting specific ...

The partial least squares (PLS) regression is a new multivariate data analysis method. In this paper, based on the ideas of PLS model and feature fusion, a new non-iterative PLS algorithm and a novel method of feature fusion are proposed. The proposed method comprises three steps: firstly, extracting two sets of feature vectors with the same pattern and establishing PLS criterion function betwe...

“Kernel Logistic PLS” (KL-PLS), a new tool for classification with performances similar to the most powerful statistical methods is described in this paper. KL-PLS is based on the principles of PLS generalized regression and learning via kernel. The successions of simple regressions, simple logistic regression and multiple logistic regressions on a small number of uncorrelated variables that ar...

This proposed tutorial, relating to the topic of quantitative research methods, will demonstrate how to use the basic and more advanced features of PLS-Graph software in the analysis of path-based Structural Equation Models (SEM) using latent variable constructs. Instructions for obtaining the PLS-Graph software (beta version 3 build 1126) will be provided to tutorial participants. PLS-Graph ma...

Drought is the most important factor limiting rice productivity in the rainfed areas of Asia. In this study, 48 pyramiding lines (PLs) and their recurrent parent, IR64, were evaluated over two years for their yield performances and related traits under severe drought stress at the reproductive stage (RS), the vegetative stage (VS) and irrigated control in order to understand the relationship be...

Using diffusion tensor (DT) magnetic resonance imaging (MRI), damage to brain intrahemispheric and interhemispheric connections was assessed in 26 sporadic primary lateral sclerosis (PLS) patients compared with 28 sporadic amyotrophic lateral sclerosis (ALS) patients with similar disability and 35 healthy controls. DT MRI diagnostic accuracy in distinguishing the two motor neuron disease (MND) ...

Partial Least Squares (PLS) has become an increasingly popular approach to testing research models with multiple proposed causality links. Moreover, recent interest in the specification of constructs in a formative manner has accentuated this tendency, given the purported ability of PLS to handle this methodological development. While a review of the literature reveals an extensive use of PLS i...