Results 51 to 60 of about 5,933,507 (244)

Local Regularization Assisted Orthogonal Least Squares Regression

, 2006
A locally regularized orthogonal least squares (LROLS) algorithm is proposed for constructing parsimonious or sparse regression models that generalize well.
Chen, S.
core   +1 more source

Orthogonal-least-squares regression: A unified approach for data modelling

, 2008
A unified approach is proposed for data modelling that includes supervised regression and classification applications as well as unsupervised probability density function estimation. The orthogonal-least-squares regression based on the leave-one-out test
Harris, C. J., X. Hong, B.L. Luk, Chen, Sheng, C.J. Harris, Chen, S., Luk, Bing L., Hong, Xia, B. L. Luk, S. Chen, Luk, B. L., Hong, X., C. J. Harris, Harris, Chris   +13 more
core   +1 more source

Prodromal Lewy Body Disorder Features in REM Sleep Behavior Disorder With Biomarker‐Defined Synucleinopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal state for Lewy body disorders and exhibits biological heterogeneity that may influence clinical expression and progression. We examined clinical features in individuals with iRBD and biomarker‐defined synucleinopathy.
Daniel Weintraub, Michele K. York, Roseanne Dobkin, Anuprita R. Nair, Ryan Kurth, David‐Erick Lafontant, Chelsea Caspell‐Garcia, Roy N. Alcalay, Ethan G. Brown, Lana M. Chahine, Christopher Coffey, Tatiana Foroud, Douglas Galasko, Karl Kieburtz, Kenneth Marek, Kalpana Merchant, Brit Mollenhauer, Kathleen L. Poston, Andrew Siderowf, Cristina Simonet, Tanya Simuni, Caroline M. Tanner, Thomas F. Tropea, Aleksandar Videnovic, The Parkinson's Progression Markers Initiative   +24 more
wiley   +1 more source

Partial Least Squares Regression Trees for Multivariate Response Data With Multicollinear Predictors

IEEE Access
Some problems arise in analyzing massive complex data consisting of multivariate response variables and a large number of multicollinear predictor variables, especially when the sample sizes compared to the number of predictors are small.
Wenxing Yu, Shin-Jae Lee, Hyungjun Cho
doaj   +1 more source

A note on between-group PCA [PDF]

, 2004
In the context of binary classification with continuous predictors, we proove two properties concerning the connections between Partial Least Squares (PLS) dimension reduction and between-group PCA, and between linear discriminant analysis and between ...
Anne-laure Boulesteix, Boulesteix, Anne-Laure   +1 more
core   +1 more source

Comprehensive Assessment of Arterial, Tissue, and Venous Collaterals for Evaluating the Infarct Growth Rate: The Multimodal Collateral Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Collaterals are crucial factors that influence the infarct growth rate (IGR). We aimed to determine whether a comprehensive multimodal collateral score (MCS), incorporating collateral assessment at the arterial, tissue, and venous levels, is associated with functional independence and provides incremental prognostic value over ...
Giorgio Busto, Umberto Pensato, Ilaria Casetta, Giorgio U. Marcello, Angelo Barra, Anna Poggesi, Edoardo Carlesi, Sara Mancini, Andrea Ginestroni, Vittorio Miele, Alessandro Padovani, Andrea Morotti, Enrico Fainardi   +12 more
wiley   +1 more source

Regularized estimation of large-scale gene association networks using graphical Gaussian models [PDF]

, 2009
Graphical Gaussian models are popular tools for the estimation of (undirected) gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of samples is the estimation of the matrix of partial ...
Schäfer, Juliane, Krämer Nicole, Kraemer, Nicole, Schaefer, Juliane, Anne-Laure Boulesteix, Boulesteix, Anne-Laure, Nicole Krämer, Juliane Schäfer, Krämer, Nicole, Boulesteix Anne-Laure, Schäfer Juliane   +10 more
core   +1 more source

Fully complex-valued radial basis function networks: orthogonal least squares regression and classification [PDF]

, 2008
We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental ...
Hong, Xia, Chen, Sheng, Harris, Chris J., Hanzo, Lajos   +3 more
core   +2 more sources

MOGAD Is the Most Common Cause of Isolated Optic Neuritis in Children

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives The study aimed to characterize the clinical features, etiologies, and outcomes of isolated, first‐time pediatric ON in the post‐MOG‐IgG era. Methods This was a single‐center retrospective cohort study at Texas Children's Hospital of patients diagnosed with first‐time ON between 2018–2024, with follow‐up data collected through 2025.
Chaitanya Aduru, Akansha Chandrasekar, Kyla Blasingame, Jonathan Rosen, Jesse M. Levine, Karla Salazar, Madhuri Chilakapati, Rod Foroozan, Victoria Hardwick, Jonathan M. Yarimi, Nikita Shukla, Timothy E. Lotze, Kristen S. Fisher, Alexander J. Sandweiss   +13 more
wiley   +1 more source

A robust partial least squares method with applications [PDF]

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.
Javier Gonzalez, Daniel Pena, Rosario Romera   +2 more
core