Results 81 to 90 of about 2,559 (181)

The Use of Hyperparameter Tuning in Model Classification: A Scientific Work Area Identification

JOIV: International Journal on Informatics Visualization
This research aims to investigate the effectiveness of hyperparameter tuning, particularly using Optuna, in enhancing the classification performance of machine learning models on scientific work reviews. The study focuses on automating the classification
Nadya Alinda Rahmi, Sarjon Defit, - Okfalisa   +2 more
doaj   +1 more source

Enhanced Modelling Performance with Boosting Ensemble Meta-Learning and Optuna Optimization

SN Computer Science
AbstractImproving modeling performance on imbalanced multi-class classification problems has continued to attract attention from researchers considering the critical and significant role such models should play in mitigating the prevalent problem. Ensemble Learning (EL) techniques are among the key methods utilized by researchers as they are known for ...
Tertsegha J. Anande, Sami Alsaadi, Mark S. Leeson   +2 more
openaire   +1 more source

Interactive segmentation of membrane and membrane‐mimic densities in cryo‐EM maps

Acta Crystallographica Section D, Volume 82, Issue 8, Page 848-861, August 2026.
SURFER performs automated segmentation of contextual membrane and membrane‐mimic density in cryo‐EM maps to enable robust separation of macromolecular signal from surrounding detergent or lipid–membrane features. It is conveniently distributed as a plugin for UCSF ChimeraX, allowing interactive application within standard map‐visualization workflows ...
Alok Bharadwaj, Lotte Veerbeek, Arjen Jakobi   +2 more
wiley   +1 more source

Otimização Multiobjetiva de um Integrador Numérico Adaptativo Utilizando o Optuna

Vetor
A integração numérica de equações diferenciais ordinárias é um dos problemas mais comuns em análise numérica. Diversos métodos e técnicas estão disponíveis na literatura, assim como diferentes combinações de heurísticas e parâmetros.
Daniel Augusto de Sousa Mendes, Rafael Pereira Bianchin, Ângelo de Carvalho Paulino, Angelo Passaro   +3 more
doaj   +1 more source

Based on the WSP-Optuna-LightGBM model for wind power prediction

Journal of Physics: Conference Series
Abstract In order to optimize energy dispatch and enhance the predictive performance of wind power forecast, this study proposes a WSP-Optuna-LightGBM mixed regression prediction model based on wind speed-power curve (WSP), Optuna parameter optimization, and Light Gradient Boosting Machine (LightGBM).
Bo Xiang, Zhenqing Liu, Linhong Huang, Ming Qin   +3 more
openaire   +1 more source

Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges

Chemical Biology &Drug Design, Volume 108, Issue 2, August 2026.
This review presents a systems‐oriented roadmap for integrating artificial intelligence into medicinal plant drug discovery to overcome persistent bottlenecks like extract complexity. It highlights that advancing toward reproducible therapeutics requires making phytochemical datasets AI‐ready via rigorous harmonization and phyto‐centric foundational ...
Amit Gangwal, Azim Ansari, Mohd Usman Mohd Siddique, Jyotiram Sawale, Suhas Padmane, Raju Wadekar   +5 more
wiley   +1 more source

Optimization of diabetes prediction methods based on combinatorial balancing algorithm

Nutrition & Diabetes
Background Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction.
HuiZhi Shao, Xiang Liu, DaShuai Zong, QingJun Song   +3 more
doaj   +1 more source

Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation

Underground Space
This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis ...
Yuxin Chen, Mohammad Hossein Kadkhodaei, Jian Zhou   +2 more
doaj   +1 more source

Temporal Drivers of Opioid‐Related ED Visits: An Ensemble Machine Learning Study With Consensus‐Based Feature Attribution

Clinical and Translational Science, Volume 19, Issue 8, August 2026.
ABSTRACT Identification of modifiable risk factors for prescription opioid use disorder (OUD)‐related emergency department (ED) visits (ICD‐10 F11.xx) is a clinical priority; however, most published models remain cross‐sectional and lack pharmacogenomic (PGx) enrichment or dual‐method feature confirmation. Using Virginia All‐Payer Claims Database (APCD)
R. Jerome Dixon, Elvin T. Price
wiley   +1 more source

Optimized Breast Cancer Classification Using PCA-LASSO Feature Selection and Ensemble Learning Strategies With Optuna Optimization

IEEE Access
Breast cancer is one of the most prevalent and life-threatening diseases among women worldwide, making early and accurate detection crucial for effective treatment.
Prabhat Kumar Sahu, Taiyaba Fatma
doaj   +1 more source