Results 71 to 80 of about 726,930 (286)

Boosting with early stopping: Convergence and consistency

, 2005
Boosting is one of the most significant advances in machine learning for classification and regression. In its original and computationally flexible version, boosting seeks to minimize empirically a loss function in a greedy fashion.
Yu, Bin, Zhang, Tong
core   +1 more source

Sarilumab in Polyarticular‐Course Juvenile Idiopathic Arthritis: Dose‐Finding and 1‐Year Analysis of a Phase 2b, Open‐Label, Multicenter Study

Arthritis Care &Research, EarlyView.
Objective This study assessed sarilumab in treating patients with polyarticular‐course juvenile idiopathic arthritis (pcJIA). Methods This phase 2b, open‐label study (NCT02776735) consisted of three sequential parts (each with a core‐treatment and extension phase).
Fabrizio De Benedetti, Inmaculada C. Penadés, Irina Nikishina, Ivan Foeldvari, Alberto J. Spindler, Anna Kozlova, Nadina Rubio‐Pérez, Pierre Quartier, Zbigniew Żuber, Raul Barria, Daniel Clemente, Gabriel V. Cornejo, Katherine Marzan, Nancy Liu, Christine Xu, Stephen DiMartino, Angeliki Giannelou, Fei Cao‐Ghoul, Bolanle Akinlade, Lydie Baret‐Cormel   +19 more
wiley   +1 more source

Comparing Person-Specific and Independent Models on Subject-Dependent and Independent Human Activity Recognition Performance

Sensors, 2020
The distinction between subject-dependent and subject-independent performance is ubiquitous in the human activity recognition (HAR) literature. We assess whether HAR models really do achieve better subject-dependent performance than subject-independent ...
Sebastian Scheurer, Salvatore Tedesco, Brendan O’Flynn, Kenneth N. Brown   +3 more
doaj   +1 more source

Investigating the Effect of Process-based Instruction of Writing on the IELTS Writing Task Two Performance of Iranian EFL Learners: Focusing on Hedging & Boosting

Cogent Education, 2021
The instruction of metadiscourse markers to L2 writers has been recommended by some scholars to assist them in employing a certain tone in persuading readers.
Mojgan Firoozjahantigh, Ebrahim Fakhri Alamdari, Amir Marzban   +2 more
doaj   +1 more source

Boosting

, 2012
An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A ...
Schapire, Robert E., Freund, Yoav
openaire   +2 more sources

Combining Three Peripheral Blood Biomarkers to Stratify Rheumatoid Arthritis–Associated Interstitial Lung Disease Risk

Arthritis Care &Research, EarlyView.
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr, Austin M. Wheeler, Brent A. Luedders, Michael Duryee, Halie Frideres, Katherine D. Wysham, Grant W. Cannon, Gary Kunkel, Dana P. Ascherman, Paul A. Monach, Gail S. Kerr, Andreas M. Reimold, Scott M. Matson, Joshua F. Baker, Geoffrey M. Thiele, Ted R. Mikuls, Bryant R. England   +16 more
wiley   +1 more source

Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems

Water Resources Research
We present an innovative approach called boosting Barlow Twins reduced order modeling (BBT‐ROM) to enhance the reliability of machine learning surrogate models for multiphase flow problems.
T. Kadeethum, V. L. S. Silva, P. Salinas, C. C. Pain, H. Yoon   +4 more
doaj   +1 more source

Condensed-gradient boosting

International Journal of Machine Learning and Cybernetics
Abstract This paper presents a computationally efficient variant of Gradient Boosting (GB) for multi-class classification and multi-output regression tasks. Standard GB uses a 1-vs-all strategy for classification tasks with more than two classes. This strategy entails that one tree per class and iteration has to be trained.
Seyedsaman Emami, Gonzalo Martínez-Muñoz   +1 more
openaire   +3 more sources

Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, EarlyView.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

Optimization by gradient boosting

, 2017
Gradient boosting is a state-of-the-art prediction technique that sequentially produces a model in the form of linear combinations of simple predictors---typically decision trees---by solving an infinite-dimensional convex optimization problem.
Biau, Gérard, Cadre, Benoît
core   +2 more sources