Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements [PDF]
Sensors, 2023 We report on the use of quartz-enhanced photoacoustic spectroscopy (QEPAS) for multi-gas detection. Photoacoustic (PA) spectra of mixtures of water (H2O), ammonia (NH3), and methane (CH4) were measured in the mid-infrared (MIR) wavelength range using a ...
Andreas N. Rasmussen +4 more
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Downscaling GRACE total water storage change using partial least squares regression [PDF]
Scientific Data, 2021 Measurement(s) Gravity Technology Type(s) gravity field theory • computational modeling technique Factor Type(s) geographic location • temporal interval Sample Characteristic - Environment water body Sample Characteristic - Location global Machine ...
Bramha Dutt Vishwakarma +2 more
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Lavender hydrosol analysis using UV spectroscopy data and partial least squares regression [PDF]
MethodsXThe aim of our work was to estimate the composition of hydrosol produced as a byproduct of lavender steam distillation using UV–Vis spectrophotometry in the 200–600 nm wavelength range through a machine learning algorithm.
Sára Preiner +3 more
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Development of partial least squares regression with discriminant analysis for software bug prediction [PDF]
HeliyonMany prediction models and approaches have been introduced during the past decades that try to forecast bugged code elements based on static source code metrics, change and history metrics, or both.
Róbert Rajkó +3 more
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Partial Least Squares Regression Performs Well in MRI-Based Individualized Estimations [PDF]
Frontiers in Neuroscience, 2019 Estimation of individuals’ cognitive, behavioral and demographic (CBD) variables based on MRI has attracted much research interest in the past decade, and effective machine learning techniques are of great importance for these estimations.
Chen Chen, Xuyu Cao, Lixia Tian
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Partial Least Squares Regression-Based Robust Forward Control of the Tableting Process [PDF]
Pharmaceutics, 2020 In this study, we established a robust feed-forward control model for the tableting process by partial least squares regression using the near-infrared (NIR) spectra and physical attributes of the granules to be compressed.
Yusuke Hattori +2 more
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Marginal Screening for Partial Least Squares Regression
IEEE Access, 2017 Partial least squares (PLS) regression is a versatile modeling approach for high-dimensional data analysis. Recently, PLS-based variable selection has attracted great attention due to high-throughput data reduction and modeling interpretability.
Naifei Zhao, Qingsong Xu, Hong Wang
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Fitting and Cross-Validating Cox Models to Censored Big Data With Missing Values Using Extensions of Partial Least Squares Regression Models [PDF]
Frontiers in Big Data, 2021 Fitting Cox models in a big data context -on a massive scale in terms of volume, intensity, and complexity exceeding the capacity of usual analytic tools-is often challenging. If some data are missing, it is even more difficult.
Frédéric Bertrand +3 more
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A fresh-cut papaya freshness prediction model based on partial least squares regression and support vector machine regression [PDF]
HeliyonThis study investigated the physicochemical and flavor quality changes in fresh-cut papaya that was stored at 4 °C. Multivariate statistical analysis was used to evaluate the freshness of fresh-cut papaya.
Liyan Rong +8 more
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HB-PLS: A statistical method for identifying biological process or pathway regulators by integrating Huber loss and Berhu penalty with partial least squares regression [PDF]
Forestry Research, 2021 Gene expression data features high dimensionality, multicollinearity, and non-Gaussian distribution noise, posing hurdles for identification of true regulatory genes controlling a biological process or pathway. In this study, we integrated the Huber loss
Wenping Deng +4 more
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