Results 101 to 110 of about 3,330 (201)

ZeroTune 2.0:Enhanced Meta-parameter Selection and Optuna Integration for Zero-Shot Hyperparameter Optimisation

Hyperparameter optimisation is crucial for maximising machine learning model performance. Still, it is computationally intensive due to the iterative nature of hyperparameter optimisation methods like SMAC, SMBOX, and frameworks like Optuna. We introduce
Salhi, Tarek, Woodward, John; id_orcid
core   +1 more source

Sentiment Analysis of Gojek Driver Application Reviews Using Support Vector Machine and Naïve Bayes with Optuna-Based Hyperparameter Tuning

Purpose – This study aims to analyze user review sentiment toward the Gojek Driver application and compare the performance of two classification algorithms, Support Vector Machine (SVM) and Naïve Bayes, using Optuna as a framework for hyperparameter ...
Nadilla Madjid, Rudi Setiawan
core   +1 more source

Forecasting grocery item sales using gradient boosting models: A study of GridSearchCV, RandomizedSearchCV, and optuna optimization approaches

Ain Shams Engineering Journal
This study introduces predictive modeling based on Extreme Gradient Boosting (XGBoost), which utilizes Optuna for hyperparameter optimization and evaluates performance against GridSearchCV and RandomizedSearchCV using a 500-day dataset.
Puja Supakar, Mitali Sarkar, Biswajit Sarkar   +2 more
doaj   +1 more source

Optuna vs Code Llama: Are LLMs a New Paradigm for Hyperparameter Tuning?

2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Optimal hyperparameter selection is critical for maximizing the performance of neural networks in computer vision, particularly as architectures become more complex. This work explores the use of large language models (LLMs) for hyperparameter optimization by fine-tuning a parameter-efficient version of Code Llama using LoRA.
Roman Kochnev, Arash Torabi Goodarzi, Zofia Antonina Bentyn, Dmitry Ignatov, Radu Timofte   +4 more
openaire   +3 more sources

PREDIKSI HARGA DAGING AYAM BROILER DI JAWA TIMUR MENGGUNAKAN METODE XGBOOST DENGAN OPTIMASI OPTUNA

Broiler chicken meat is one of the most widely consumed poultry commodities in Indonesia due to its affordable price and abundant availability. However, broiler chicken prices often experience significant fluctuations due to various factors, such as the ...
Salsabilah, Elina
core  

Ionospheric TEC Prediction in low-latitude Indian region during geomagnetic storm periods based on XGBoost with Optuna framework and comparison with IRI-Plas 2020

This paper introduces a strong 24-hour TEC forecast model based on the Extreme Gradient Boosting (XGBoost) algorithm, implemented for GPS-based TEC data at both the IISC and Chum stations.
Kumar, S. Kishore, Jude, Andrew F., Kenisha, J., Logesh, S., Dass, Sarat C.; id_orcid, Muthukumaran, T., Mukesh, R., Kiruthiga, S., Cynthia, G.   +8 more
core   +1 more source

Interpretable machine learning for predicting EUR of shale gas wells in the Weiyuan block

Scientific Reports
For shale gas development, it is essential to clarify the main controlling factors of EUR and realize its accurate prediction. Based on data from 123 wells in the Weiyuan block, this study combines Pearson correlation analysis, RF-RFE algorithm, and ...
Sijie He, Feifei Fang, Jin Chang, Xizhe Li, Ruilan Luo, Nijun Qi   +5 more
doaj   +1 more source

Optuna ML Framework for SCBA Concrete Strength

International Journal of Concrete Structures and Materials
The cement industry plays a crucial role in global CO2 emissions. As demand for cement continues to rise, innovative solutions are required to mitigate its environmental impact.
Isaac Ajibola Fakoya, Abidemi Bashiru Folorunsho, Seungwon Kim, Cheolwoo Park   +3 more
doaj   +1 more source

An Optuna-Based Metaheuristic Optimization Framework for Biomedical Image Analysis

Engineering, Technology & Applied Science Research
The success of Deep Learning (DL) in biomedical imaging heavily relies on optimal hyperparameter selection, which remains a complex and computationally intensive challenge. This paper introduces a metaheuristic-inspired Optuna framework for efficient hyperparameter optimization and validates its effectiveness using U-Net as a case study for brain MRI ...
openaire   +1 more source

GWtuna: Trawling through the data to find Gravitational Waves with Optuna and Jax

GWtuna is a fast gravitational-wave search prototype built on Optuna (optimisation software library) and JAX (accelerator-orientated array computation library) [1, 2]. Using Optuna, we introduce black box optimisation algorithms and evolutionary strategy algorithms to the gravitational-wave community.
Green, Susanna, Lundgren, Andrew
openaire   +2 more sources