Results 61 to 70 of about 57,263 (295)
The elastic net: Stability for sparsity methods [PDF]
, 2010 In recent years, methods for sparse approximation have gained considerable attention and have been successfully applied to numerous problems in various mathematical disciplines.This work starts by illustrating applications for sparse approximation to ...
Schiffler, Stefan
core
MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis
FEBS Open Bio, EarlyView.MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss +7 more
wiley +1 more source
Elastic net regularization: Predictors of SF-36 pain subscale. [PDF]
, 2021 Elastic net regularization: Predictors of SF-36 pain subscale.
Hannah M. Zipprich (10453778) +4 more
core +1 more source
Zero-Inflated Binary Classification Model with Elastic Net Regularization
MathematicsZero inflation and overfitting can reduce the accuracy rate of using machine learning models for characterizing binary data sets. A zero-inflated Bernoulli (ZIBer) model can be the right model to characterize zero-inflated binary data sets.
Hua Xin +3 more
doaj +1 more source
eLife, 2023 Background: Machine learning (ML) techniques improve disease prediction by identifying the most relevant features in multidimensional data. We compared the accuracy of ML algorithms for predicting incident diabetic kidney disease (DKD).
Charumathi Sabanayagam +6 more
doaj +1 more source
Learning performance of elastic-net regularization
Mathematical and Computer Modelling, 2013 In this paper, within the framework of statistical learning theory we address the elastic-net regularization problem. Based on the capacity assumption of hypothesis space composed by infinite features, significant contributions are made in several aspects.
Yu-long Zhao, Yun-Long Feng
openaire +1 more source
Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach +23 more
wiley +1 more source
Regularization and variable selection via the elastic net [PDF]
, 2005 We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation.
Hui Zou, Trevor Hastie
core +1 more source
Penalized Poisson Regression Model using adaptive modified Elastic Net Penalty [PDF]
, 2015 Variable selection in count data using penalized Poisson regression is one of the challenges in applying Poisson regression model when the explanatory variables are correlated.
Algamal, Zakariya Yahya; Department of Statistics and Informatics-University of Mosel
core +4 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source