Partial least squares (PLS)
Extended Locality Preserving Partial Least Squares with Class Information
... The PLS method in its traditional form does not consider the local information of data. To tackle this problem, a new dimension reduc- tion method called Locality preserving partial least squares ...
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Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach
... and partial least squares analysis (PLS, Lohmöller 1989) constitute the two corresponding, yet distinctive (Schneeweiß 1991), statistical techniques for assessing cause- effect-relationship-models ...
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Probabilistic partial least squares model: Identifiability, estimation and application
... sets, Partial Least Squares (PLS) regression [28] is a popular dimension reduction method ...[28]. Partial Least Squares is popular in chemometrics ...
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A Partial Least Squares based algorithm for parsimonious variable selection
... using Partial Least Squares, where the focus is to obtain a hard, and at the same time stable, selection of ...at least as good as three alternative methods, Forward, Lasso and ST-PLS, on the ...
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Analysis of partial least squares algorithm based on SBM DEA
... The T 2 ellipse assisted analysis method of the partial least squares (PLS) is able to recognize the noise, however, it fails to analyze the noise in the multidimensional space. In the paper, we ...
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Multi-label Classification Using Hypergraph Orthonormalized Partial Least Squares
... methods, Partial Least Squares (PLS) [9] and Canonical Correlation Analysis (CCA) [8] are two representative ones, which are used for finding the relationships between two sets of ...
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Fuel park wastewater monitoring with UV-Vis spectra and partial least squares models
... of Partial Least Squares (PLS) calibration models for four environmental monitoring parameters, namely, Chemical Oxygen Demand (COD), 5-day Bio- chemical Oxygen Demand (BOD 5 ), Total ...
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Key issues on Partial Least Squares (PLS) in operations management research: A guide to submissions
... Extending structural equations models based on composites (PLS-SEM) has been widely diffused of late in areas like marketing (Hair, Sarstedt, Ringle & Mena, 2012b; Henseler, Ringle & Sinkovics, 2009; Hult, Hair, ...
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M-Government Adoption Factors in the UAE: a Partial Least Squares Approach
... This study investigates the factors that influence the intention of citizens of the United Arab Emirates (UAE) to use a mobile government (mGov) platform. The UAE is one of the leading countries that offer this service ...
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Partial least squares based gene expression analysis in renal failure
... detect dysregulated genes. This statistical procedure ignored unaccounted array specific factors, including various biological, environmental factors. Previous studies [7,8] have suggested that partial ...
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Decoupling Multivariable Processes using Partial Least Squares for Decentralized Control
... Partial Least Squares (PLS) finds latent variables that are associated with the maximum variation in process data and provides diagonal pairings of latent variables as strong as ...
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Kernel Partial Least Squares for Stationary Data
... that partial least squares algorithm is competitive with other regression methods such as ridge regression and principal component regression, needing generally fewer iterations than the latter to ...
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Analysis of TCM Data Based on Partial Least Squares within Random Forest
... Partial Least Squares(PLS) [6,7] can well explain the data with the characteristic of multi-independent variables and multiple dependent variables, but the principal components extract from PLS is ...
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Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... named partial least square model averaging ...apply partial least squares (PLS) to reduce and transform original explanatory variables become new variables called components, then these ...
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Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling
... in partial least squares structural equation modeling (PLS-SEM; Wold 1982) whose usage has recently gained momentum in international marketing (Richter et ...two-stage least squares ...
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Person re identification using partial least squares appearance modelling
... a Partial Least Squares Regression model to predict the skeleton of a person, allowing us to prioritise features from a person’s limbs rather than from the ...
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Speech Emotion Recognition with MPCA and Kernel Partial Least Squares Regression
... Abstract—Speech signal is one of the major means for communication which carries not only semantic, but personal information , such as genders and emotions. The researches about speech emotion have become more and more ...
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Modeling individual HRTF tensor using high order partial least squares
... high-order partial least squares (HOPLS), aiming to seek a joint subspace approximation for both the selected parameters and the individual core ...the partial least squares ...
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Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space
... Classical PCR, PLS and RR techniques are well known shrinkage estimators designed to deal with multicollinearity (see, e.g., Frank and Friedman, 1993, Montgomery and Peck, 1992, Jolliffe, 1986). The multicollinearity or ...
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Determination of Hexazinone in Environmental Samples by Uv-Vis Spectrophotometry-Partial Least Squares Regression
... To define the optimal number of factors required to construct the calibration models, PRESS (Prediction Error Sum of Squares) was drawn in function of the ten factors to be evaluated. The results are shown in ...
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