Results 21 to 30 of about 880,930 (320)
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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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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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 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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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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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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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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The Degrees of Freedom of Partial Least Squares Regression [PDF]
, 2010 The derivation of statistical properties for Partial Least Squares regression can be a challenging task. The reason is that the construction of latent components from the predictor variables also depends on the response variable.
Akaike H. +6 more
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A robust partial least squares method with applications [PDF]
, 2007 Partial least squares regression (PLS) is a linear regression technique developed to relate many regressors to one or several response variables. Robust methods are introduced to reduce or remove the effect of outlying data points.
González, Javier +2 more
core +4 more sources