Search results for "Partial least squares regression"

showing 10 items of 122 documents

Near Infrared Spectroscopy Detection and Quantification of Herbal Medicines Adulterated with Sibutramine.

2015

There is an increasing demand for herbal medicines in weight loss treatment. Some synthetic chemicals, such as sibutramine (SB), have been detected as adulterants in herbal formulations. In this study, two strategies using near infrared (NIR) spectroscopy have been developed to evaluate potential adulteration of herbal medicines with SB: a qualitative screening approach and a quantitative methodology based on multivariate calibration. Samples were composed by products commercialized as herbal medicines, as well as by laboratory adulterated samples. Spectra were obtained in the range of 14,000-4000 per cm. Using PLS-DA, a correct classification of 100% was achieved for the external validatio…

Spectroscopy Near-InfraredInjury controlTraditional medicinebusiness.industryQuantitative methodologyNear-infrared spectroscopyExternal validationPoison controlMultivariate calibrationDiscriminant AnalysisPathology and Forensic MedicinePartial least squares regressionAppetite DepressantsGeneticsmedicineLinear ModelsPlant PreparationsbusinessDrug ContaminationCyclobutanesSibutraminemedicine.drugJournal of forensic sciences
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Testing of the region of Murcia soils by near infrared diffuse reflectance spectroscopy and chemometrics.

2008

A partial least squares near infrared (PLS-NIR) method has been developed for the determination of several physicochemical parameters in soils from different locations of the Region of Murcia. The method was based on the proper chemometric treatment of diffuse reflectance spectra of soil samples. Reflectance spectra were scanned from samples stored in glass vials in the NIR region between 800 and 2600 nm, averaging 36 scans per spectrum at a resolution of 8 cm(-1). Models were built using reference data of 39 samples selected from a dendrogram obtained after hierarchical cluster analysis of NIR spectra of soils and prediction parameters were established from a validation set of 109 addition…

Spectroscopy Near-InfraredSoil testDiffuse reflectance infrared fourier transformChemistryNear-infrared spectroscopyAnalytical chemistryMineralogyInfrared spectroscopyAnalytical ChemistryChemometricsSoilMetalsPartial least squares regressionDiffuse reflectionOrganic ChemicalsSpectroscopyTalanta
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Partial least squares modelization of energy dispersive X-ray fluorescence.

2019

As a proof of concept, a green methodology has been developed for the energy dispersive X-ray fluorescence (ED-XRF) determination of calcium, potassium, iron, magnesium, aluminum, chromium, strontium, phosphorus and nickel in the peel of untreated kaki fruit (Diospyros kaki. L) samples. ED-XRF spectra of fifty-six kakis purchased in the local area of LLombay (Valencia) were obtained directly from samples without any previous treatment and without sample damage just after cleaning the fruit with distilled water. Inductively Couple Plasma Optical Emission Spectrometry (ICP-OES) was used as a reference method to determine the mineral elements after microwave assisted acid digestion. XRF spectr…

StrontiumMagnesium010401 analytical chemistryAnalytical chemistrychemistry.chemical_elementDiospyros kakiX-ray fluorescence02 engineering and technology021001 nanoscience & nanotechnology01 natural sciences0104 chemical sciencesAnalytical ChemistryChromiumchemistryDistilled waterInductively coupled plasma atomic emission spectroscopyPartial least squares regression0210 nano-technologyTalanta
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Análisis de métodos de validación cruzada para la obtención robusta de parámetros biofísicos

2015

[EN] Non-parametric regression methods are powerful statistical methods to retrieve biophysical parameters from remote sensing measurements. However, their performance can be affected by what has been presented during the training phase. To ensure robust retrievals, various cross-validation sub-sampling methods are often used, which allow to evaluate the model with subsets of the field dataset. Here, two types of cross-validation techniques were analyzed in the development of non-parametric regression models: hold-out and k-fold. Selected non-parametric linear regression methods were least squares Linear Regression (LR) and Partial Least Squares Regression (PLSR), and nonlinear methods were…

TeledeteccióGeography Planning and Developmentlcsh:G1-922Least squaresCross-validationValidación cruzadaProcesos gausianosHold-outAnàlisi de regressióLinear regressionStatisticsPartial least squares regressionEarth and Planetary Sciences (miscellaneous)MLRAbusiness.industryCross-validationRegression analysisPattern recognitionRegresión de Kernel RidgeAprendizaje automáticoRegressionK-foldHold-OutGeographyk-foldPrincipal component regressionArtificial intelligencebusinessKernel Ridge regressionNonlinear regressionGaussian process regressionlcsh:Geography (General)Revista de Teledetección
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Assessing the territorial influence of an Iberian worship site. The chemical characterisation of the terracotta from the Iron Age sanctuary of La Ser…

2017

This paper presents the study of the prestigious terracotta votive figurines from the Iberian Iron Age sanctuary of La Serreta (Alicante province, Spain) composed of 174 items. Portable X-ray fluorescence (PXRF) was used to identify elemental markers that permit us to observe the differences between local and non-local terracotta figurines and furthermore to evaluate the geographical influence of the La Serreta sanctuary using Principal Component Analysis (PCA). The Partial Least Squares Discriminant Analysis (PLSDA) statistical method was also used to classify the figurines of uncertain geographical origin. The resulting groups were related to typological and stylistic groups of figurines …

TerracottaAlicanteArcheology060102 archaeologyTerritorial influence010308 nuclear & particles physicsmedia_common.quotation_subjectLa Serreta06 humanities and the artsLinear discriminant analysisWorship01 natural sciencesArchaeologyArqueologíaGeographyIron Agevisual_art0103 physical sciencesPartial least squares regressionPrincipal component analysisvisual_art.visual_art_medium0601 history and archaeologyIberian Iron Age sanctuaryTerracottamedia_common
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A rapid method for the differentiation of yeast cells grown under carbon and nitrogen-limited conditions by means of partial least squares discrimina…

2012

This paper shows the ease of application and usefulness of mid-IR measurements for the investigation of orthogonal cell states on the example of the analysis of Pichia pastoris cells. A rapid method for the discrimination of entire yeast cells grown under carbon and nitrogen-limited conditions based on the direct acquisition of mid-IR spectra and partial least squares discriminant analysis (PLS-DA) is described. The obtained PLS-DA model was extensively validated employing two different validation strategies: (i) statistical validation employing a method based on permutation testing and (ii) external validation splitting the available data into two independent sub-sets. The Variable Importa…

Time FactorsChemistry(all)Spectrophotometry InfraredNitrogenAnalytical chemistryInfrared spectroscopyPichiaArticleAnalytical ChemistryPichia pastorisPichia pastorisInfrared (IR) micro-spectroscopyPartial least squares regressionProcess controlPartial least squares-discriminant analysis (PLS-DA)Least-Squares AnalysisProjection (set theory)Cell ProliferationPrincipal Component AnalysisbiologyChemistryDiscriminant AnalysisReproducibility of ResultsLinear discriminant analysisbiology.organism_classificationDouble cross validation (2CV)YeastCarbonYeastCulture MediaPermutation testingPrincipal component analysisFeasibility StudiesBiological systemTalanta
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Prediction of organic carbon and total nitrogen contents in organic wastes and their composts by Infrared spectroscopy and partial least square regre…

2017

Middle and near infrared (MIR and NIR) were employed to determine organic carbon (OC) and total nitrogen (TN) in different soil organic amendments including wastes, composts and mixtures of composts and organic wastes. Prediction models based on partial least squares (PLS) regression from the spectra of untreated samples were built. Different spectra preprocessing strategies were adopted and the best number of latent variable was evaluated using leave-one-out cross-validation. Attenuated total reflectance (PLS-ATR-MIR) and diffuse reflectance (PLS-DR-NIR) models were built and evaluated from root mean square error of cross validation and prediction (RMSECV and RMSEP), coefficients of determ…

Total organic carbonMean squared errorChemistryAnalytical chemistryInfrared spectroscopy04 agricultural and veterinary sciences010501 environmental sciencesResidual01 natural sciencesCross-validationAnalytical ChemistryAttenuated total reflectionPartial least squares regression040103 agronomy & agricultureTotal nitrogen0401 agriculture forestry and fisheries0105 earth and related environmental sciencesTalanta
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Feature Selection Approach based on Mutual Information and Partial Least Squares

2014

Feature selection technology can improve the modeling accuracy and reduce model’s complexity, especially for the high dimensional spectral data. Aim at this problem, feature selection approach based on mutual information (MI) and partial least square (PLS) is proposed in this paper. MI values between features and responsible variable are calculated, and the threshold value using to select final features is optimal selected based on PLS algorithm. The numbers of the latent values of the PLS and the threshold value of MI are selected according the modeling performance simultaneously. The experimental results based on the near-infrared spectrum show that the proposed approach has better perfor…

Variable (computer science)Threshold limit valuebusiness.industryPartial least squares regressionGeneral EngineeringPattern recognitionFeature selectionHigh dimensionalArtificial intelligenceMutual informationSpectral databusinessMathematicsAdvanced Materials Research
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Evaluation of the effect of chance correlations on variable selection using Partial Least Squares -Discriminant Analysis

2013

Variable subset selection is often mandatory in high throughput metabolomics and proteomics. However, depending on the variable to sample ratio there is a significant susceptibility of variable selection towards chance correlations. The evaluation of the predictive capabilities of PLSDA models estimated by cross-validation after feature selection provides overly optimistic results if the selection is performed on the entire set and no external validation set is available. In this work, a simulation of the statistical null hypothesis is proposed to test whether the discrimination capability of a PLSDA model after variable selection estimated by cross-validation is statistically higher than t…

Variable selectionESTADISTICA E INVESTIGACION OPERATIVAFeature selectionChance correlationsAnalytical ChemistrySet (abstract data type)ResamplingPartial least squares regressionStatisticsHumansMetabolomicsLeast-Squares AnalysisSelection (genetic algorithm)ProbabilityGaucher DiseaseModels StatisticalChemistryDiscriminant AnalysisReproducibility of ResultsPartial Least Squares-Discriminant Analysis (PLSDA)Linear discriminant analysisVariable (computer science)Null hypothesisAlgorithmsSoftware
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Partial least squares-near infrared determination of pesticides in commercial formulations

2007

Abstract A solvent free, fast and environmentally friendly near infrared-based methodology (NIR) was developed for pesticide determination in commercially available formulations. This methodology was based on the direct measurement of the diffuse reflectance spectra of solid samples and a multivariate calibration model (partial least squares, PLS) to determine the active principle concentration in commercial formulations. The PLS calibration set was built on using the spiked samples by mixing different amounts of pesticide standards and powdered samples. Buprofezin, Diuron and Daminozide were used as test analytes. Concentration of Buprofezin in the samples was calculated employing a 4-fact…

Waste generationRoot mean squareAnalytechemistry.chemical_compoundChromatographyChemistryPartial least squares regressionNear-infrared spectroscopyCalibrationAnalytical chemistryDaminozidePesticideSpectroscopyVibrational Spectroscopy
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