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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.
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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.

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ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

TL;DR: This web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures.
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NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

TL;DR: The developments in data acquisition and multivariate analysis of NMR-based metabolomics data are described, with particular emphasis on the metabolomics of Cerebrospinal Fluid and biomarker discovery in Multiple Sclerosis.
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Sensor arrays for liquid sensing – electronic tongue systems

TL;DR: These topics are summarized in this review: miniaturization of electronic tongues and hybrid systems for liquid sensing, as well as approaches embracing mass- and optical-sensors, and various pattern recognition systems were proposed.
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Quantitative analysis of salt-affected soil reflectance spectra: A comparison of two adaptive methods (PLSR and ANN)

TL;DR: In this article, partial least squares regression (PLSR) and artificial neural network (ANN) were compared in order to examine linear and non-linear relationship between soil reflectance and salt concentration.
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NIR spectroscopy applications for internal and external quality analysis of citrus fruit - A review

TL;DR: Research progress on NIRS applications in internal and external quality measurement of citrus fruit, including the selection of NIR characteristics for spectra capture, analysis and interpretation are reviewed.
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

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.
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