Chemometric methods in analytical spectroscopy technology
Y Huang - Chemometric Methods in Analytical Spectroscopy …, 2022 - Springer
In recent decades, with the rapid development of artificial intelligence, data mining, and
cloud computing, new chemometric methods have sprung up and become one of the fastest …
cloud computing, new chemometric methods have sprung up and become one of the fastest …
High‐dimensional QSAR prediction of anticancer potency of imidazo [4, 5‐b] pyridine derivatives using adjusted adaptive LASSO
In high‐dimensional quantitative structure–activity relationship (QSAR) studies, identifying
relevant molecular descriptors is a major goal. In this study, a proposed penalized method is …
relevant molecular descriptors is a major goal. In this study, a proposed penalized method is …
Interpretation of high-dimensional linear regression: Effects of nullspace and regularization demonstrated on battery data
High-dimensional linear regression is important in many scientific fields. This article
considers discrete measured data of underlying smooth latent processes, as is often …
considers discrete measured data of underlying smooth latent processes, as is often …
Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples
Y Liu, W Cai, X Shao - Spectrochimica Acta Part A: Molecular and …, 2016 - Elsevier
Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy
because the measurements of the spectra may be performed on different instruments and …
because the measurements of the spectra may be performed on different instruments and …
Quantitative structure–activity relationship model for prediction study of corrosion inhibition efficiency using two‐stage sparse multiple linear regression
A new quantitative structure–activity relationship (QSAR) of the inhibition of mild steel
corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two …
corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two …
A novel molecular descriptor selection method in QSAR classification model based on weighted penalized logistic regression
ZY Algamal, MH Lee - Journal of Chemometrics, 2017 - Wiley Online Library
Molecular descriptor selection is a pivotal tool for quantitative structure–activity relationship
modeling. This paper proposes a novel molecular descriptor selection method on the basis …
modeling. This paper proposes a novel molecular descriptor selection method on the basis …
Comparison of several strategies for the deployment of a multivariate regression model on several handheld NIR instruments. Application to the quality control of …
Chemometrics applied to spectroscopic measurements such as near-infrared are gaining
more and more importance for quality control of pharmaceutical products. Handheld near …
more and more importance for quality control of pharmaceutical products. Handheld near …
High‐dimensional quantitative structure–activity relationship modeling of influenza neuraminidase a/PR/8/34 (H1N1) inhibitors based on a two‐stage adaptive …
Outliers in the biological activity variable or the heavy tailed distribution of the error are often
encountered in practice. Under these circumstances, the quantittative structure–activity …
encountered in practice. Under these circumstances, the quantittative structure–activity …
Near-infrared calibration transfer via support vector machine and transfer learning
Y Binfeng, J Haibo - Analytical Methods, 2015 - pubs.rsc.org
Support Vector Regression (SVR) has been widely used as a nonlinear regression method
in multivariate calibration. This paper investigates the transfer of SVR models between …
in multivariate calibration. This paper investigates the transfer of SVR models between …
Standardization of near infrared spectra based on multi-task learning
B Yu, H Ji, Y Kang - Spectroscopy Letters, 2016 - Taylor & Francis
In order to model the near infrared spectral difference between two instruments, this paper
presents an approach based on multi-task learning for multivariate instrument …
presents an approach based on multi-task learning for multivariate instrument …