Results 11 to 20 of about 3,984,806 (250)
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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Partial Least Squares Enhances Genomic Prediction of New Environments
Frontiers in Genetics, 2022 In plant breeding, the need to improve the prediction of future seasons or new locations and/or environments, also denoted as “leave one environment out,” is of paramount importance to increase the genetic gain in breeding programs and contribute to food
Osval A. Montesinos-López +8 more
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Completions of ε-Dense Partial Latin Squares [PDF]
, 2013 A classical question in combinatorics is the following: given a partial Latin square $P$, when can we complete $P$ to a Latin square $L$? In this paper, we investigate the class of textbf{$epsilon$-dense partial Latin squares}: partial Latin squares in
Bartlett, Padraic James +2 more
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Penerapan Partial Least Squares Pada Data Gingerol
ComTech, 2010 Multivariate calibration model aims to predict the expensive measures obtained by using the measures of a cheap and easy. There are several problems that often occur in the model calibration, among others, and multikolinear. To overcome these problems we
Margaretha Ohyver
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Partial Least Squares Optimization Method Integrating Restricted Boltzmann Machine [PDF]
Jisuanji gongcheng, 2017 Partial Least Squares(PLS) method adopts Principal Component Analysis(PCA),it cannot express the nonlinear characteristic,and the prediction accuracy is low in the nonlinear data.Based on this,an analysis and predicting method combining Restricted ...
ZHU Zhipeng,DU Jianqiang,YU Riyue,NIE Bin
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Locality preserving partial least squares discriminant analysis for face recognition
Journal of King Saud University: Computer and Information Sciences, 2022 We propose a locality preserving partial least squares discriminant analysis (LPPLSDA) which adds a locality preserving feature to the conventional partial least squares discriminant analysis(PLS-DA).
Muhammad Aminu, Noor Atinah Ahmad
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Multi-trait genome prediction of new environments with partial least squares
Frontiers in Genetics, 2022 The genomic selection (GS) methodology proposed over 20 years ago by Meuwissen et al. (Genetics, 2001) has revolutionized plant breeding. A predictive methodology that trains statistical machine learning algorithms with phenotypic and genotypic data of a
Osval A. Montesinos-López +6 more
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Fault identification for chiller sensor based on partial least square method [PDF]
E3S Web of Conferences, 2021 Sensor failures can lead to an imbalance in heating, ventilation and air conditioning (HVAC) control systems and increase energy consumption. The partial least squares algorithm is a multivariate statistical method, compared with the principal component ...
Wu Bang +4 more
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PARTIAL LEAST SQUARES REGRESSION $PLS$ ON INTERVAL DATA
Revista de la Facultad de Ciencias, 2016 Uncertainty in the data can be considered as a numerical interval in which a variable can assume its possible values, this has been known as interval data. In this paper the $PLS$ regression methodology is extended to the case where explanatory, response
Carlos Alberto Gaviria-Peña +2 more
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Partial least-squares regression for soil salinity mapping in Bangladesh
Ecological Indicators, 2023 Estimating the salinity of the soil along the coast of south-western Bangladesh is the focus of this study. Thirteen soil salinity indicators were computed using the Landsat OLI images, and 241 soil salinity samples were gathered from secondary sources ...
Showmitra Kumar Sarkar +3 more
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