Journal ArticleDOI
PLS-regression: a basic tool of chemometrics
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TLDR
PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.About:
This article is published in Chemometrics and Intelligent Laboratory Systems.The article was published on 2001-10-28. It has received 7861 citations till now. The article focuses on the topics: Partial least squares regression.read more
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Journal ArticleDOI
Human muscle spindles act as forward sensory models.
Michael Dimitriou,Benoni B. Edin +1 more
TL;DR: It is shown that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle, and muscle spindles can act as "forward sensory models", which implies learning how to control not only the skeletal muscles but also the fusimotor system.
Journal ArticleDOI
Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm
TL;DR: In this paper, the authors developed a fast and robust methodology to analyse the biogas production process with respect to the significant process variables using the ant colony optimisation algorithm with the help of ant colony optimization algorithm.
Journal ArticleDOI
Classification of Amazonian rosewood essential oil by Raman spectroscopy and PLS-DA with reliability estimation
TL;DR: Test the applicability of Raman spectroscopy and Partial Least Square Discriminant Analysis (PLS-DA) as means to classify the essential oil extracted from different parties (wood, leaves and branches) of the Brazilian tree A. rosaeodora to find the best model.
Journal ArticleDOI
A hybrid variable selection strategy based on continuous shrinkage of variable space in multivariate calibration.
Yong-Huan Yun,Yong-Huan Yun,Jun Bin,Dongli Liu,Lin Xu,Ting-Liang Yan,Dong-Sheng Cao,Qing-Song Xu +7 more
TL;DR: The results show that VCPA-GA andVCPA-IRIV significantly improve model's prediction performance when compared with other methods, indicating that the modified VCPA step is a very efficient way to filter the uninformative variables and VC PA-based hybrid strategy is a good and promising strategy for variable selection in NIR.
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DrugPred: A Structure-Based Approach To Predict Protein Druggability Developed Using an Extensive Nonredundant Data Set
TL;DR: A structure-based druggability predictor (DrugPred) using partial least-squares projection to latent structures discriminant analysis (PLS-DA) and the method is robust against conformational changes in the binding site and outperforms previously published methods.
References
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Book
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
TL;DR: In this article, the authors present a method for detecting and assessing Collinearity of observations and outliers in the context of extensions to the Wikipedia corpus, based on the concept of Influential Observations.
Book
A User's Guide to Principal Components
TL;DR: In this paper, the authors present a directory of Symbols and Definitions for PCA, as well as some classic examples of PCA applications, such as: linear models, regression PCA of predictor variables, and analysis of variance PCA for Response Variables.
Journal ArticleDOI
A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
Bradley Efron,Gail Gong +1 more
TL;DR: This paper reviewed the nonparametric estimation of statistical error, mainly the bias and standard error of an estimator, or the error rate of a prediction rule, at a relaxed mathematical level, omitting most proofs, regularity conditions and technical details.