Results 71 to 80 of about 106,398 (294)
Machine learning regression models for internal shame
Acta PsychologicaThis study aims to predict Internal Shame (IS) based on childhood trauma, social emotional competence, cognitive flexibility, distress tolerance and alexithymia in an Iranian sample.
Nataša Kovač +3 more
doaj +1 more source
Big Data and Cognitive Computing, 2022 Gradient boosting ensembles have been used in the cyber-security area for many years; nonetheless, their efficacy and accuracy for intrusion detection systems (IDSs) remain questionable, particularly when dealing with problems involving imbalanced data ...
Maya Hilda Lestari Louk, Bayu Adhi Tama
doaj +1 more source
Enhancing Bubble Removal in Geometry‐Optimized Electrodes
Advanced Engineering Materials, EarlyView.3D‐printed lattice electrodes outperform stochastic foams in alkaline water electrolysis despite 20%–25% lower surface area. Straight flow channels generate Venturi‐like bubble entrainment, suppressing gas accumulation that renders foam interiors electrochemically inactive.
Florian Wiesner +5 more
wiley +1 more source
Infinitesimal gradient boosting
, 2021 44 pages, 1 figureWe define infinitesimal gradient boosting as a limit of the popular tree-based gradient boosting algorithm from machine learning. The limit is considered in the vanishing-learning-rate asymptotic, that is when the learning rate tends to
Dombry, Clément, Duchamps, Jean-Jil
core
TBR Data for GRADIENT BOOSTING MACHINES
, 2023 This data set contains the data point used in the work 'DEVELOPMENT OF GRADIENT BOOSTING MACHINES FOR ESTIMATION OF TOTAL AND DYNAMIC LIQUID HOLDUP IN TRICKLE BED ...
Bharath Sureshkumar +4 more
core +1 more source
Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure
Advanced Engineering Materials, EarlyView.Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari +3 more
wiley +1 more source
Machine Learning Approaches for Fatigue Life Prediction of Steel and Feature Importance Analyses
InfrastructuresPredicting fatigue behavior in steel components is highly challenging due to the nonlinear and uncertain nature of material degradation under cyclic loading.
Babak Naeim +6 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Gradient Boosting Machine: A Survey
CoRR, 2019 In this survey, we discuss several different types of gradient boosting algorithms and illustrate their mathematical frameworks in detail: 1. introduction of gradient boosting leads to 2. objective function optimization, 3. loss function estimations, and 4. model constructions. 5. application of boosting in ranking.
Zhiyuan He +3 more
openaire +2 more sources
Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions
Advanced Functional Materials, EarlyView.This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian +7 more
wiley +1 more source