Partial Least Squares Discriminant Analysis
Near Infrared Spectroscopy Coupled with Kernel Partial Least Squares Discriminant Analysis for Rapid Screening Water Containing Malathion
... Y = K U (13) If the mode uses to be an indicator vector coding two classes: −1 for members of Class A, 1 for members of Class B, a kernel partial least squares-discriminant analysis ...
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Multivariate pharmacokinetic/pharmacodynamic (PKPD) analysis with metabolomics shows multiple effects of remoxipride in rats
... data analysis mostly is performed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) (Bartel et ...Component Analysis ...
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A type 2 biomarker separates relapsing-remitting from secondary progressive multiple sclerosis
... B partial least squares discriminant analysis plots (darker hue) overlaid with Set C prediction results (lighter hue); misclassified patients are shown with open ...(blue ...
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Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES
... i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for ...
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Application of Direct Immersion Solid-Phase Microextraction (DI-SPME) for Understanding Biological Changes of Mediterranean Fruit Fly (Ceratitis capitata) During Mating Procedures
... component analysis (PCA), sparse partial least squares-discriminant analysis (sPLS-DA), and heat map and ANOVA analyses were used in these ...
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Chemometric Feature Selection and Classification of Ganoderma lucidum Spores and Fruiting Body Using ATR FTIR Spectroscopy
... penalized discriminant analysis (PDA) model was developed to identify informative spectral features for distinguishing between spores and fruiting body of ...component discriminant analysis ...
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<p>Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma</p>
... data analysis to accurately and objec- tively identify and distinguish benign and malignant thyroid ...data analysis, such as PCA-LDA and Lasso-partial least squares- ...
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Cross-sectional examination of metabolites and metabolic phenotypes in uremia
... partial least squares discriminant analysis (PLS-DA) to visualize the linear components that discriminate individ- uals across the categories (tertiles or class) of metabolic ...
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Vol 1, No 3-4 (2012)
... The high separation power, and relatively simple instrumentation of capillary electrophoresis (CE) and related technologies facilitated their successful application in many fields of up-to-date scientific research such ...
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Classification of Hungarian medieval silver coins using x-ray fluorescent spectroscopy and multivariate data analysis
... component analysis, linear discriminant analysis, partial least squares discriminant analysis, classification and regression trees and multivariate curve resolution ...
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A fitness index for transplantation of machine perfused cadaveric rat livers
... multi-way partial least squares discriminant analysis (MPLSDA) model to assess what the acceptable degree of ischemic damage of each liver was for successful transplantation (> 1 ...
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Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
... Figure 1 models the causal relationship between the observations D and the variables f and t, such that the distribution p( f,t | D , ) can be decomposed into noise model p ( t | y,f) and prior p ( f | X), disregarding ...
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Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... regression analysis when number of observations is smaller than number of explanatory variables (also known as high-dimensional ...proposed partial least squares model averaging (PLSMA) as an ...
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Rapid detection of total nitrogen content in soy sauce using NIR spectroscopy
... using partial least squares (PLS) regression with ...interval partial least square (Si-PLS) algorithm was performed by Chen et ...interval partial least squares ...
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“Data Mining techniques differentiation between NPPLS and PLS”
... The COL is a highly ill-conditioned data set. The best model for this data set is the Partial Least Squares (PLS), built with two factors. Among all the models that are below the condition number of ...
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Some aspects of progeny testing Southdown rams : a thesis presented in part fulfilment of the requirements for the degree of Master of Agricultural Science in Massey University of Manawatu, New Zealand
... Least squares means, least squares deviations of sire groups from the means, least squares differences due to birthrank and sex, and partial regression coefficients for the characteristi[r] ...
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Analysis of partial least squares algorithm based on SBM DEA
... increase; ( , x x 1 2 , L , x p ) is the input. Then, (2) is adopted to solve ρ of the decision making unit. For a sample, we call the sample as the effective sample if ρ = 1 , namely, the effective value of the SBM ...
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Kernel Partial Least Squares for Stationary Data
... the partial least squares and the conjugate gradient ...kernel partial least squares and kernel conjugate ...kernel partial least squares is shown with the ...
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Lists in a Lighthouse
... After all UV-Vis absorbance spectra had been preprocessed using the techniques described in the previous section, PCA was performed to reduce the dimensionality of the data. A requirement for LDA calculations is to have ...
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Deformation analysis with Total Least Squares
... Table 4 summarises the significance tests for the deforma- tion points regarding the both LS and GTLS methods. The test criterion is the fractile value of the t-distribution with 95% confidence level and relevant degree ...
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