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Partial least squares regression

Known as: PLS, Projection to latent structures, Partial Linear Squares 
Partial least squares regression (PLS regression) is a statistical method that bears some relation to principal components regression; instead of… 
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Related topics

Related topics

18 relations
Causal inferenceChemometricsData miningFeature extraction

Broader (1)

Least squares

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Forecasting Stock Price Using Partial Least Squares Regression
Financial markets are systems where buyers and sellers interact and various transactions of ownership claims (stocks) takes place… 
2017
2017
Partial Least Squares Regression in Payment Default Prediction
Payment default is affected by many interrelated factors. When concentrating on financial data, payment default can be predicted… 
2008
2008
3D face shape approximation from intensities using Partial Least Squares
In this paper, we apply partial least squares (PLS) regression to predict 3D face shape from a single image. PLS describes the… 
2007
2007
Summary of Partial Least Squares Regression
The partial least squares is introduced and summarized.The direct solution method of partial least squares and the partial least… 
2006
2006
Use of Partial Least Squares Regression and Multidimensional Scaling on Aroma Models of California Chardonnay Wines
The aroma models of California Chardonnay wines were developed and evaluated using multivariate statistical procedures to… 
2005
2005
Theory and Application of Partial Least Squares Regression
Objective To study the theory and application of partial least squares regression (PLS). To compare PLS with principal component… 
2004
2004
Combined use of partial least squares regression and neural network for diagnosis tasks
This work deals with a diagnosis system, based on a combined use of partial least squares regression (PLS) and neural network (NN… 
2003
2003
Sparse Kernel Partial Least Squares Regression
Partial Least Squares Regression (PLS) and its kernel version (KPLS) have become competitive regression approaches. KPLS performs… 
Highly Cited
2001
Highly Cited
2001
Prediction of basic wood properties for Norway spruce. Interpretation of Near Infrared Spectroscopy data using partial least squares regression
Abstract This work was undertaken to investigate the feasibility of using near infrared spectroscopy (NIR) and partial least… 
2000
2000
Drift Reduction For Metal-Oxide Sensor Arrays Using Canonical Correlation Regression And Partial Least Squares
The transient response of metal-oxide sensors exposed to mild odours can be oftentimes highly correlated with the behaviour of… 
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