partial least squares
An Introduction to Partial Least Squares Regression
... Partial least squares (PLS) is a method for construct- ing predictive models when the factors are many and highly collinear. Note that the emphasis is on pre- dicting the responses and not ...
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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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Thermal-to-visible face recognition using partial least squares
... histogram of oriented gradients (HOG), followed by partial least squares (PLS)-based model building. We further improve the cross-modal recognition accuracy by incorporating ther- mal cross-examples. ...
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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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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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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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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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Multi-label Classification Using Hypergraph Orthonormalized Partial Least Squares
... and Partial Least Squares (PLS) [9, 25] in this paper, we concentrate on a variant of PLS, named Orthonormalized Partial Least Squares (OPLS) [10], which imposes the orthogonal ...
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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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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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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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Analysis of TCM Data Based on Partial Least Squares within Random Forest
... We compared our improved algorithm (RFR-PLS) to the other three methods, which is the classic Partial Least Squares(PLS), Random Forest(RF) and the method of Fusing Model Tree into Partial ...
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Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach
... Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical ...segment-specific partial ...
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Kernel Partial Least Squares for Stationary Data
... kernel partial least squares estimator to the true regression function when the input data are not independent and identically distributed, but rather stationary time ...
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Probabilistic partial least squares model: Identifiability, estimation and application
... With a rapid increase in volume and complexity of data sets, there is a need for methods that can extract useful information, for example the relationship between two data sets measured for the same persons. 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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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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The critical success factors for organizational performance of SMEs in Malaysia: a partial least squares approach
... To investigate the relationship between critical success factors (Top Management Support, Customer Focus, Employee Orientation, Technology Orientation, and Entrepreneurial Orientatio[r] ...
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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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