Results 111 to 120 of about 4,993,128 (318)
Elastic Net based Feature Ranking and Selection
CoRR, 2020 Feature selection is important in data representation and intelligent diagnosis. Elastic net is one of the most widely used feature selectors. However, the features selected are dependant on the training data, and their weights dedicated for regularized regression are irrelevant to their importance if used for feature ranking, that degrades the model ...
Shaode Yu +7 more
openaire +2 more sources
Prediction of protein-protein interactions based on elastic net and deep forest
bioRxiv, 2020 Prediction of protein-protein interactions (PPIs) helps to grasp molecular roots of disease. However, web-lab experiments to predict PPIs are limited and costly.
Bin Yu +5 more
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Evaluation of the lasso and the elastic net in genome-wide association studies
Frontiers in Genetics, 2013 The number of publications performing genome-wide association studies (GWAS) has increased dramatically. Penalized regression approaches have been developed to overcome the challenges caused by the high dimensional data, but these methods are relatively ...
Patrik eWaldmann +5 more
doaj +1 more source
Sensors, 2020 A novel multi-classification method, which integrates the elastic net and probabilistic support vector machine, was proposed to solve this problem in cancer detection with gene expression profile data of platelets, whose problems mainly are a kind of ...
Lei-ming Yuan, Yiye Sun, Guangzao Huang
doaj +1 more source
Sparsity-accuracy trade-off in MKL [PDF]
, 2009 We empirically investigate the best trade-off between sparse and uniformly-weighted multiple kernel learning (MKL) using the elastic-net regularization on real and simulated datasets.
Suzuki, Taiji, Tomioka, Ryota
core
Properties and iterative methods for the elastic net with ℓp-norm errors [PDF]
, 2020 Liling Wei, Hong‐Kun Xu
openalex +1 more source
Numerical Exploration of Thermal Shock Resistance in MgO–C Refractories
Advanced Engineering Materials, EarlyView.A mesostructure‐resolved numerical framework is developed to evaluate the thermal shock resistance of MgO–C refractories. By modeling interface debonding under rapid temperature changes and introducing a modified thermal shock parameter that accounts for mesocracks, the study shows how graphite content and aggregate size influence thermal shock ...
Jishnu Vinayak Gopi +3 more
wiley +1 more source
Hydrogen‐Assisted Fracture of Iron‐Based Fe–Ni–Al Alloys
Advanced Engineering Materials, EarlyView.Principal relations and fracture mechanisms of single‐phase and precipitate‐strengthened Fe–Ni–Al alloys subjected to prior electrochemical hydrogen charging are identified. The mechanisms of hydrogen effect on strength and microhardness are discussed, including hydrogen‐induced increase in microhardness and the role of hydrogen in fracture behavior ...
Nataliya Yadzhak +3 more
wiley +1 more source
Fatigue Crack Initiation and Growth in Nanocrystalline Ni at Multiple Length‐Scales
Advanced Engineering Materials, EarlyView.Overview of miniaturized in situ SEM fatigue setup and resultant fatigue crack growth data for nanocrystalline Ni. The presented study focuses on the analysis of fatigue crack growth rate (FCGR) in focused ion beam‐notched microcantilevers prepared from nanocrystalline (NC) Ni as a model material.
Igor Moravcik +7 more
wiley +1 more source