PLS (Partial Least Squares) Methods
A Comparative Analysis of Partial Least Squares (PLS) Regression and Artificial Neural Network (ANN) Methods for Determining Elemental Weights in Sheet Metal.
... and Partial Least Squares. Both methods present an opportunity to build mathematical models that not only describe the spectroscopic data of the calibrated samples, but will also help predict ...
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... QSAR methods including multiple linear regression (MLR), partial least squares combined with genetic algorithm for variable selection (GA- PLS), factor analysis–MLR (FA-MLR), principal ...
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The relationship between climate change and wars waged between nomadic and farming groups from the Western Han Dynasty to the Tang Dynasty period
... on partial least squares (PLS) methods at centennial timescales (smoothed by a 5-point fast Fourier transform (FFT) filter) (Ge et ...
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SPECTROMETRIC DETERMINATION OF SOME HEAVY METALS IN COSMETIC PRODUCTS FOUND BY PRINCIPAL COMPONENT REGRESSION AND PARTIAL LEAST SQUARES METHODS
... Partial least squares (PLS) are the widely used regression method in chemometrics ...a PLS calibration it is known that information from the concentration values is introduced into the ...
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Comparison of Different Regularized and Shrinkage Regression Methods to Predict Daily Tropospheric Ozone Concentration in the Grand Casablanca Area
... alternative methods to the classical Multiple Linear Regression (MLR) that circumvent the problem of multicollinearity which is likely to lead to unstable ...[14], Partial Least Squares ...
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Design, optimization, and validation of chemometrics-assisted spectrophotometric methods for simultaneous determination of etodolac and thiocolchicoside in pharmaceuticals
... calibration partial least squares (PLS), principal component regression (PCR), and inverse least squares (ILS) was developed for the simultaneous analysis of ET and TC without ...
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Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space
... kernel PLS and kernel PCR achieves the optimal results on the testing set compared to kernel ...projection methods; i.e. kernel PLS and kernel ...
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Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy
... and partial least squares (PLS) multivariate ...These methods provide powerful tools for the selection of more promising samples for further research and ...
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“Data Mining techniques differentiation between NPPLS and PLS”
... technique, Partial Least Squares (PLS) and one nonlinear technique(NLPLS)) on two different and unique data sets: a collinear data set (called "the COL" data set in this paper) and a ...
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A Comparison Study of Ridge Regression and Principle Component Regression with Application
... estimation methods ridge regression (RR), principle component regression (PCR), and Latent Root LR ...the partial least squares (PLS) regression as an alternative procedure for handling ...
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Lee07c
... Table I summarizes the results from the proposed method as well as the results from the PCR and stepwise regression methods. The PCR method does not conduct variable selection, but it was included here as an ...
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SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF RABEPRAZOLE SODIUM AND DOMPERIDONE MALEATE IN CAPSULES BY CHEMOMETRIC METHODS
... by partial least-squares (PLS) and principal component regression (PCR) methods do not require any priori graphical treatment of the overlapping spectra of two drugs in the ...
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Application of FTIR Spectrometry Using Multivariate Analysis For Prediction Fuel in Engine Oil
... mathematic‑statistical methods to the results of chemical measuring for the purpose of extracting as much relevant information as possible from the chemical data (Sejkorová, ...multivariate methods are ...
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Comparative qsar analysis of histone deacetylase 6 (hdac6) inhibitors as anti cancer agents
... besides Partial east Squares regression (PLS) methods, in addition to a 3D QSAR model which was developed using k-Nearest Neighbor Molecular Field Analysis ...
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Particle swarm optimized partial least square support vector regression model for tax revenue prediction
... CV methods is to make the whole sample set randomly divided into K groups, then making the K − 1 groups as the training set and the rest group as a test ...
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... Computational chemistry is unique method in drug discovery which reduce cost. In this study 86 molecules containing isatin core were subjected to quantitative structure-activity relationship analysis and docking study to ...
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An Optimized BP Algorithm Based on PLS
... We have known data [10], to forecast the occurrence degree of the wheat blossom midge. Here we choose the data of 15 samples from 1986 to 2000 as the study object, use x1-x14 to represent the 14 feature variables ...
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Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting, and Benchmarking
... the methods were ...genomic methods had very similar accuracy in traits 1 and 3, once SEs were ...was PLS, which showed slightly lower ...across methods in traits 1 and 3. However, in traits 2 ...
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... mentioned methods is a difficult problem since there usually exist spectral ...Recently, partial least squares (PLS) to multivariate chemical data, as a widespread quantitative ...
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Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... proposed partial least squares model averaging (PLSMA) as an approach to construct candidate models, while partial least squares (PLS) method was applied during that ...
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