Search Results - "Journal of chemometrics"

Comparison of the variable importance in projection (VIP) and of the selectivity ratio (SR) methods for variable selection and interpretation by Farrés, Mireia, Platikanov, Stefan, Tsakovski, Stefan, Tauler, Romà

“…This study compares the application of two variable selection methods in partial least squares regression (PLSR), the variable importance in projection (VIP)…”
Get full text

Partial least squares discriminant analysis: taking the magic away by Brereton, Richard G., Lloyd, Gavin R.

“…Partial least squares discriminant analysis (PLS‐DA) has been available for nearly 20 years yet is poorly understood by most users. By simple examples, it is…”
Get full text

Comparison of variable selection methods in partial least squares regression by Mehmood, Tahir, Sæbø, Solve, Liland, Kristian Hovde

“…Through the remarkable progress in technology, it is getting easier and easier to generate vast amounts of variables from a given sample. The selection of…”
Get full text

One‐dimensional convolutional neural networks for spectroscopic signal regression by Malek, Salim, Melgani, Farid, Bazi, Yakoub

“…This paper proposes a novel approach for driving chemometric analyses from spectroscopic data and based on a convolutional neural network (CNN) architecture…”
Get full text

Preprocessing methods for near‐infrared spectrum calibration by Jiao, Yiping, Li, Zhichao, Chen, Xisong, Fei, Shumin

“…Spectrum preprocessing is an essential component in the near‐infrared (NIR) calibration. However, it has mostly been configured arbitrarily in the literature…”
Get full text

VSN: Variable sorting for normalization by Rabatel, Gilles, Marini, Federico, Walczak, Beata, Roger, Jean‐Michel

“…Spectrometric and analytical techniques in general collect multivariate signals from chemical or biological materials by means of a specific measurement…”
Get full text

Variable influence on projection (VIP) for orthogonal projections to latent structures (OPLS) by Galindo-Prieto, Beatriz, Eriksson, Lennart, Trygg, Johan

“…A new approach for variable influence on projection (VIP) is described, which takes full advantage of the orthogonal projections to latent structures (OPLS)…”
Get full text

Variable selection in regression-a tutorial by Andersen, C. M., Bro, R.

“…This paper provides a practical guide to variable selection in chemometrics with a focus on regression‐based calibration models. Several approaches, such as…”
Get full text

Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models? by Roy, Kunal, Ambure, Pravin, Kar, Supratik, Ojha, Probir Kumar

“…Quantitative structure‐activity/property/toxicity relationship (QSAR/QSPR/QSTR) models are effectively employed to fill data gaps by predicting a given…”
Get full text

Chemometrics in laser‐induced breakdown spectroscopy by Zhang, Tianlong, Tang, Hongsheng, Li, Hua

“…Laser‐induced breakdown spectroscopy (LIBS) is a new type of elemental analytical technology with the advantages of real‐time, online, and noncontact as well…”
Get full text

Modified ridge‐type estimator to combat multicollinearity: Application to chemical data by Lukman, Adewale F., Ayinde, Kayode, Binuomote, Samuel, Clement, Onate A.

“…The Linear regression model is one of the most widely used models in different fields of study. The most popularly used estimation technique is the ordinary…”
Get full text

Machine learning in prediction of intrinsic aqueous solubility of drug‐like compounds: Generalization, complexity, or predictive ability? by Lovrić, Mario, Pavlović, Kristina, Žuvela, Petar, Spataru, Adrian, Lučić, Bono, Kern, Roman, Wong, Ming Wah

“…We present a collection of publicly available intrinsic aqueous solubility data of 829 drug‐like compounds. Four different machine learning algorithms (random…”
Get full text

PhotoMetrix and colorimetric image analysis using smartphones by Böck, Fernanda Carla, Helfer, Gilson Augusto, Costa, Adilson Ben, Dessuy, Morgana Bazzan, Ferrão, Marco Flôres

“…The steady advances in technology employed in smartphones, coupled with the high availability and the ease access to these devices, increased the interest in…”
Get full text

Common and distinct components in data fusion by Smilde, Age K., Måge, Ingrid, Næs, Tormod, Hankemeier, Thomas, Lips, Mirjam Anne, Kiers, Henk A. L., Acar, Ervim, Bro, Rasmus

“…In many areas of science, multiple sets of data are collected pertaining to the same system. Examples are food products that are characterized by different…”
Get full text

Chemometrics‐assisted color histogram‐based analytical systems by Gonçalves Dias Diniz, Paulo Henrique

“…This review systematizes for the first time the here called “Chemometrics‐assisted color histogram‐based analytical systems” under the acronym CACHAS. A…”
Get full text

SO‐CovSel: A novel method for variable selection in a multiblock framework by Biancolillo, Alessandra, Marini, Federico, Roger, Jean‐Michel

“…With the development of technology and the relatively higher availability of new instrumentations, having multiblock data sets (eg, a set of samples analyzed…”
Get full text

Modified PCA and PLS: Towards a better classification in Raman spectroscopy–based biological applications by Guo, Shuxia, Rösch, Petra, Popp, Jürgen, Bocklitz, Thomas

“…Raman spectra of biological samples often exhibit variations originating from changes of spectrometers, measurement conditions, and cultivation conditions…”
Get full text

Multi‐similarity measurement driven ensemble just‐in‐time learning for soft sensing of industrial processes by Yuan, Xiaofeng, Zhou, Jiao, Wang, Yalin, Yang, Chunhua

“…Just‐in‐time learning (JITL) technique has been widely used for adaptive soft sensing of nonlinear processes. It builds online local model with the most…”
Get full text

CV-ANOVA for significance testing of PLS and OPLS® models by Eriksson, Lennart, Trygg, Johan, Wold, Svante

“…This report describes significance testing for PLS and OPLS® (orthogonal PLS) models. The testing is applicable to single‐Y cases and is based on ANOVA of the…”
Get full text

A practical convolutional neural network model for discriminating Raman spectra of human and animal blood by Dong, Jialin, Hong, Mingjian, Xu, Yi, Zheng, Xiangquan

“…A practical convolutional neural network (CNN) model is proposed to discriminate the Raman spectra of human and animal blood. The proposed network, which…”
Get full text