This paper addresses the problem of online quality prediction in processes with multiple operating modes. The paper proposes a new method called mixture of partial least squares regression (Mix-PLS), where the solution of the mixture of experts regression is performed using the partial least squares (PLS) algorithm. The PLS is used to tune the model experts and the gate parameters. The solution...

Partial Least Squares (PLS) is a standard statistical method in chemometrics. It can be considered as an incomplete, or “partial”, version of the Least Squares estimator of regression, applicable when high or perfect multicollinearity is present in the predictor variables. The Least Squares estimator is well-known to be an optimal estimator for regression, but only when the error terms are norm...

Inhibitory activity against aldose reductase enzyme of nineteen flavonoid derivatives was subjected to classical quantitative structure activity relationship (QSAR) analysis using electrotopological state (E-state) atom parameter. For the development of the QSAR models, statistical techniques like stepwise multiple linear regression and partial least squares (PLS) were used. The best equation i...

Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and bagging approaches. In this paper the random forests approach is extended for variable selection with other learning models, in this case Partial Least Squares (PLS) and Kernel Partial Least Squares (K-PLS) to estimat...

chemometric techniques in spectral analysis have gained importance in the quality control of  the drugs mixtures and pharmaceutical formulations containing two or more drugs with overlapping spectra. since theophylline and etophylline have common chromophore, they cannot be analyzed simultaneously using conventional uv methods. simultaneous spectrophotometric determination of etophylline and th...

in the present work we study the use of fourier transform near infrared spectroscopy (ftnirs)technique to analysis the calcium (ca), phosphorus (p) and copper (cu) contents offish meal. the regression methods employed were partial least squares (pls) and kernelpartial least squares (kpls). the results showed that the efficiency of kpls was better thanpls. as a whole, the application of ft-nirs ...

When dealing with graphical Gaussian models for gene regulatory networks, the major problem is to compute the matrix of partial correlations. Based on the close connection between partial correlations and least squares regression, we suggest estimation of high-dimensional gene networks in terms of partial least squares (PLS) regression and the adaptive Lasso, respectively. In a simulation study...

Model performance of the partial least squares method (PLS) alone and bagging-PLS was investigated in online near-infrared (NIR) sensor monitoring of pilot-scale extraction process in Fructus aurantii. High-performance liquid chromatography (HPLC) was used as a reference method to identify the active pharmaceutical ingredients: naringin, hesperidin and neohesperidin. Several preprocessing metho...

We propose a novel framework that combines penalization techniques with Partial Least Squares (PLS). We focus on two important applications. (1) We combine PLS with a roughness penalty to estimate high-dimensional regression problems with functional predictors and scalar response. (2) Starting with an additive model, we expand each variable in terms of a generous number of B-Spline basis functi...