Results 111 to 120 of about 108,016 (310)
kernlab - An S4 package for kernel methods in R [PDF]
, 2004 kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 object model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels),
Zeileis, Achim +10 more
core +1 more source
Comparison of Triply Periodic Minimal Surface Energy Absorbers Under Uniaxial Compressive Loading
Advanced Engineering Materials, EarlyView.This study investigates LCD 3D printed Triply Periodic Minimal Surface (TPMS) structures as mechanical energy absorbers. By comparing various base designs and layered combinations under uniaxial compression, it identifies that a Diamond‐Gyroid sandwich structure offers superior performance.
Sergej Grednev +2 more
wiley +1 more source
Support vector machines and generalisation in HEP
Journal of Physics: Conference Series, 2016 We review the concept of support vector machines (SVMs) and discuss examples of their use. One of the benefits of SVM algorithms, compared with neural networks and decision trees is that they can be less susceptible to over fitting than those other algorithms are to over training. This issue is related to the generalisation of a multivariate algorithm (
Agni Bethani +3 more
openaire +3 more sources
Breast Tumor Susceptibility to Chemotherapy via Support Vector Machines
, 2003 Support vector machines (SVMs), utilizing RNA signature measurements, were used to generate a classi er to distinguish breast cancer patients that are partial-responders to chemotherapy treatment, from patients that are nonresponders.
Mangasarian, Olvi, Fung, Glenn
core
Advanced Functional Materials, EarlyView.We propose a suture‐complementary approach that integrates optical skin clearing with a strain‐programmable luminescent adhesive patch. Hyaluronic acid promotes transdermal delivery of tartrazine to improve optical clearing and stabilizes its interaction with a photosensitizer. Optical clearing increases the penetration depth of visible light into skin,
Seong‐Jong Kim +6 more
wiley +1 more source
Hybrid Quantum Technologies for Quantum Support Vector Machines
InformationQuantum computing has rapidly gained prominence for its unprecedented computational efficiency in solving specific problems when compared to classical computing counterparts.
Filippo Orazi +3 more
doaj +1 more source
The Default Risk of Firms Examined with Smooth Support Vector Machines [PDF]
In the era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the bank's objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error)
Yuh-Jye Lee +3 more
core
Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System [PDF]
, 2008 —This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation
Mohamed , Azah +2 more
core
Advanced Functional Materials, EarlyView.Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
Least Squares Minimum Class Variance Support Vector Machines
ComputersIn this paper, we propose a Support Vector Machine (SVM)-type algorithm, which is statistically faster among other common algorithms in the family of SVM algorithms. The new algorithm uses distributional information of each class and, therefore, combines
Michalis Panayides, Andreas Artemiou
doaj +1 more source