A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a support vector classifier. Unlike principal component analysis (PCA), which has previously served as a dimension reduction step for discrimination problems, orthonormalized PLS is closely related to Fisher’s approach t...

The aim of this work is to show how partial least squares (PLS) regression when combined with two other techniques Karhunen-Loeve (KL) expansion and Markov chain Monte Carlo (MCMC) can be efficient and effective at addressing parameter uncertainties that affect the predictive ability of a model for critical applications such as monitoring and control. We introduce a combination of PLS regressio...

Analysis of images involving humans is of significant interest in computer vision because problems such as detection, modeling, recognition, and tracking are fundamental to model interactions between people and understand highlevel activities. Visual information contained in images is generally represented using feature descriptors. Many general classes of descriptors have been proposed focusin...

Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table. When the goal is to find the shared information between two tables, the ap...

Mango is a kind of popular tropical fruit, and the soluble solid content is an important in this study visible and short-wave near-infrared spectroscopy (VIS/SWNIR) technique was applied. For sake of investigating the feasibility of using VIS/SWNIR spectroscopy to measure the soluble solid content in mango, and validating the performance of selected sensitive bands, for the calibration set was ...

Quantitative analysis for the flue gas of natural gas-fired generator is significant for energy conservation and emission reduction. The traditional partial least squares method may not deal with the nonlinear problems effectively. In the paper, a nonlinear partial least squares method with extended input based on radial basis function neural network (RBFNN) is used for components prediction of...

quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (fa-mlr), principle component regression analysis (pcra), and genetic algorithm-partial least squares ga-pls. the fa-mlr describes the effect of geometrical and quantum indices on enzyme inhibition act...

A and Marakas [ A3 Aguirre-Urreta M, Marakas G (2013) Research note—Partial least squares and models with formatively specified endogenous constructs: A cautionary note. Inform. Systems Res., ePub ahead of print September 5, http://dx.doi.org/10.1287/isre.2013.0493] aim to evaluate the performance of partial least squares (PLS) path modeling when estimating models with formative endogenous cons...

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...

An application of e-tongue based on porphyrin electropolymers for the detection of Primitivo and Negroamaro wines defects related to the presence of “off-odor” methiol (3(methylthio)-propanol), isoamyl alcohol fusel oil, the marker of the yeast activity benzaldehyde and vinegar formation marker acetic acid was investigated. The best results were obtained for acetic acid and isoamyl alcohol. Fur...