Results 41 to 50 of about 718,596 (262)

Comment: Boosting Algorithms: Regularization, Prediction and Model Fitting

, 2008
The authors are doing the readers of Statistical Science a true service with a well-written and up-to-date overview of boosting that originated with the seminal algorithms of Freund and Schapire. Equally, we are grateful for high-level software that will
Buja, Andreas, Mease, David, Wyner, Abraham J.   +2 more
core   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

POISSON MIXED MODELS WITH A BOOSTING APPROACH FOR THE ANALYSIS OF COUNT DATA

Barekeng
Boosting is a powerful technique for enhancing predictive accuracy by iteratively reweighting observations, and is particularly effective in high-dimensional settings and for variable selection.
Ita Wulandari, Khairil Anwar Notodiputro, Bagus Sartono, Anwar Fitrianto, Anang Kurnia   +4 more
doaj   +1 more source

Data-Based Sensing and Stochastic Analysis of Biodiesel Production Process

Energies, 2018
Biodiesel production is a field of outstanding prospects due to the renewable nature of its feedstock and little to no overall CO2 emissions to the environment.
Iftikhar Ahmad, Ahsan Ayub, Uzair Ibrahim, Mansoor Khan Khattak, Manabu Kano   +4 more
doaj   +1 more source

Explainability of a Machine Learning Granting Scoring Model in Peer-to-Peer Lending

IEEE Access, 2020
Peer-to-peer (P2P) lending demands effective and explainable credit risk models. Typical machine learning algorithms offer high prediction performance, but most of them lack explanatory power.
Miller Janny Ariza-Garzon, Javier Arroyo, Antonio Caparrini, Maria-Jesus Segovia-Vargas   +3 more
doaj   +1 more source

Variable selection methods for identifying predictor interactions in data with repeatedly measured binary outcomes

Journal of Clinical and Translational Science, 2021
Introduction: Identifying predictors of patient outcomes evaluated over time may require modeling interactions among variables while addressing within-subject correlation. Generalized linear mixed models (GLMMs) and generalized estimating equations (GEEs)
Bethany J. Wolf, Yunyun Jiang, Sylvia H. Wilson, Jim C. Oates   +3 more
doaj   +1 more source

Totally Corrective Multiclass Boosting with Binary Weak Learners [PDF]

, 2010
In this work, we propose a new optimization framework for multiclass boosting learning. In the literature, AdaBoost.MO and AdaBoost.ECC are the two successful multiclass boosting algorithms, which can use binary weak learners.
Barnes, Nick, Hao, Zhihui, Shen, Chunhua, Wang, Bo   +3 more
core  

Colorectal cancer‐derived FGF19 is a metabolically active serum biomarker that exerts enteroendocrine effects on mouse liver

Molecular Oncology, EarlyView.
Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley, Michael W. Rohr, Joseph A. Goode, Sai Preethi Nakkina, Jignesh G. Parikh, Deborah A. Altomare   +5 more
wiley   +1 more source

Enhancing Premier League Match Outcome Prediction Using Support Vector Machine with Ensemble Techniques: A Comparative Study on Bagging and Boosting

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Predicting football match outcomes is a significant challenge in sports analytics, requiring models that are both accurate and resilient. This study evaluates the effectiveness of ensemble techniques, specifically Bagging and Boosting, in enhancing the ...
Agus Perdana Windarto, Putrama Alkhairi, Johan Muslim   +2 more
doaj   +1 more source

Performance Analysis of Classification Algorithms on Birth Dataset

IEEE Access, 2020
Generating intuitions from data using data mining and machine learning algorithms to predict outcomes is useful area of computing. The application area of data mining techniques and machine learning is wide ranging including industries, healthcare ...
Syed Ali Abbas, Aqeel Ur Rehman, Fiaz Majeed, Abdul Majid, M. Sheraz Arshed Malik, Zaki Hassan Kazmi, Seemab Zafar   +6 more
doaj   +1 more source