Results 11 to 20 of about 1,984 (174)

Improving the prediction of bitumen’s density and thermal expansion by optimizing artificial neural networks with Optuna and TensorFlow [PDF]

MethodsX
Previous work demonstrated that Random Forest Regressors (RFRs) could estimate the physical properties of bitumen using molecular descriptors derived from Molecular Dynamics (MD) simulations, thereby reducing the need for computationally intensive ...
Eli I. Assaf, Xueyan Liu, Sandra Erkens
doaj   +2 more sources

Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization

Smart Agricultural Technology
Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South ...
Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi   +2 more
doaj   +3 more sources

Hyperparameter Tuning with Optuna to optimize the YOLOv11n Model for Weed Detection

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Accurate weed detection is essential for maintaining the cleanliness and aesthetic appeal of residential yards. This study aimed to optimize YOLOv11n, a lightweight object detection model, to achieve high precision in weed identification under real-world
Candhy Fadhila Arsyad, Pulung Nurtantio Andono, Moch Arief Soeleman   +2 more
doaj   +2 more sources

Enhancing Liver Cirrhosis Staging Accuracy using Optuna-Optimized TabNet

Journal of Applied Informatics and Computing
Liver cirrhosis is a progressive chronic disease whose early detection poses a clinical challenge, making accurate severity staging crucial for patient management.
Muhammad Farhan Arifin, Ika Novita Dewi, Abu Salam, Danang Wahyu Utomo, Sindhu Rakasiwi   +4 more
doaj   +2 more sources

An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest

Geomatics, Natural Hazards & Risk
This study proposed an interpretable model that combines Random Forest (RF), Optuna hyperparameter optimization, and SHapley Additive exPlanations (SHAP) to achieve optimal landslide susceptibility evaluation and provide explanations in the northwest ...
Xin Xiao, Yi Zou, Jiangcheng Huang, Xuan Luo, Luyi Yang, Meng Li, Pengwu Yang, Xuan Ji, Yungang Li   +8 more
doaj   +3 more sources

Optuna: Finding the optimal hyperparameters

, 2023
Application of Optuna to find the optimal hyperparameters for transfer learning or fine tuning the pre-trained models This code was used to find best hyperparameters to classify MS and Normal cases using SLO images. However it can be used in any other application.
Aghababaei Ali, Arian Roya, Kafieh Rahele   +2 more
openaire   +2 more sources

Optuna

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
The purpose of this study is to introduce new design-criteria for next-generation hyperparameter optimization software. The criteria we propose include (1) define-by-run API that allows users to construct the parameter search space dynamically, (2) efficient implementation of both searching and pruning strategies, and (3) easy-to-setup, versatile ...
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama   +4 more
openaire   +2 more sources

OOG- Optuna Optimized GAN Sampling Technique for Tabular Imbalanced Malware Data

2022 IEEE International Conference on Big Data (Big Data), 2022
Cyberspace occupies a large portion of people's life in the age of modern technology, and while there are those who utilize it for good, there are also those who do not. Malware is an application whose construction was not motivated by a benign goal and it can harm, steal, or even alter personal information and secure applications and software.
S. M. Towhidul Islam Tonmoy, S. M. Mehedi Zaman   +1 more
openaire   +2 more sources

A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023
The performance of machine learning (ML) methods for classification and regression tasks applied to tabular datasets is sensitive to hyperparameters values.
Prativa Pokhrel, Alina Lazar
doaj   +1 more source

Efficient Hyperparameter Optimization for Reference Evapotranspiration Estimation with Limited Parameters: A Comparison of Optuna and Grid Search in the Doukkala Region, Morocco [PDF]

E3S Web of Conferences
Accurate estimation of reference evapotranspiration (ETo) is essential for irrigation scheduling and water resource management, particularly in semi-arid regions where meteorological data are often limited.
Belarbi Zaid, El Younoussi Yacine
doaj   +1 more source