Results 21 to 30 of about 886,403 (293)
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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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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Regularized Partial Least Squares with an Application to NMR Spectroscopy [PDF]
, 2012 High-dimensional data common in genomics, proteomics, and chemometrics often contains complicated correlation structures. Recently, partial least squares (PLS) and Sparse PLS methods have gained attention in these areas as dimension reduction techniques ...
Allen, Genevera I. +3 more
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Partial least squares regression in the social sciences [PDF]
Tutorials in Quantitative Methods for Psychology, 2015 Partial least square regression (PLSR) is a statistical modeling technique that extracts latent factors to explain both predictor and response variation.
Megan L. Sawatsky +2 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 discriminant analysis: A dimensionality reduction method to classify hyperspectral data [PDF]
, 2018 The recent development of more sophisticated spectroscopic methods allows acqui- sition of high dimensional datasets from which valuable information may be extracted using multivariate statistical analyses, such as dimensionality reduction and automatic ...
Bellincontro, Andrea +2 more
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Evaluation of Partial Least Squares Parameter Recovery [PDF]
, 2015 The purpose of this study was to evaluate the performance of Partial Least Squares under lessthan-ideal conditions selected to imitate real-world data. A simulation study with a 3×3×2×2 design was conducted.
Chumney, Frances
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Neural Legal Outcome Prediction with Partial Least Squares Compression
Stats, 2020 Predicting the outcome of a case from a set of factual data is a common goal in legal knowledge discovery. In practice, solving this task is most of the time difficult due to the scarcity of labeled datasets. Additionally, processing long documents often
Charles Condevaux
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