نتایج جستجو برای: partial least squares pls method
تعداد نتایج: 2140492 فیلتر نتایج به سال:
Variable selection is important in fine tuning partial least squares (PLS) regression models. This study introduces a novel variable weighting method for PLS regression where the univariate response variable y is used to guide the variable weighting in a recursive manner—the method is called recursive weighted PLS or just rPLS. The method iteratively reweights the variables using the regression...
partial least squares modeling as a powerful multivariate statistical tool was applied tothe simultaneous spectrophotometric determination of silicate and phosphate in aqueoussolutions. the concentration range for silicate and phosphate were 0.02-0.6 and 0.4-3 μg ml-1,respectively. the experimental calibration set was composed with 30 sample solutions using amixture design for two component mix...
Speaker recognition systems have been shown to work well when recordings are collected in conditions with relatively limited mismatch. Thus, a significant focus of the current research is techniques for robust system performance when greater variability is present. This study considers a diverse data set with recordings collected in multiple different rooms with different types of microphones. ...
A method for the simultaneous determination of the colorants Sunset Yellow FCF and Quinoline Yellow using solid-phase spectrophotometry is proposed. The colorants were isolated in Sephadex DEAE A-25 gel at pH 5.0, the gel-colorants system was packed in a 1 mm silica cell and spectra were recorded between 400 and 600 nm against a blank. Statistical results were obtained by partial least squares ...
Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS wer...
Purpose – Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PL...
A family of regularized least squares regression models in a Reproducing Kernel Hilbert Space is extended by the kernel partial least squares (PLS) regression model. Similar to principal components regression (PCR), PLS is a method based on the projection of input (explanatory) variables to the latent variables (components). However, in contrast to PCR, PLS creates the components by modeling th...
کالیبراسیون چند متغیره یادگیری چگونگی ترکیب داده ه از چندین کانال مختلف است ، تا بر مسائل انتخاب گری فایق آمده و دیدگاهی جدید بدست آید، همچنین توانایی کنترل و حذف مقادیر خارج از محدوده را بدست آوریم. یکی از مثالهایی از کاربرد کالیبراسیون چند متغیره در اینجا معرفی شده است . در این کار با استفاده از رگرسیون حداقل مربعات جزئی (plsr),(partial least squares regression) به اندازه گیری همزمان اسپکتروف...
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