Results 31 to 40 of about 4,087 (203)

Hyperparameter Tuning for Address Validation using Optuna

WSEAS TRANSACTIONS ON COMPUTER RESEARCH, 2023
Public institutions generally share personal information on their websites. That allows the possibility to find personal information when performing internet searches quickly. However, the personal information that is on the internet is not always accurate and can lead to misunderstandings and ambiguity concerning the accessible postal address ...
openaire   +3 more sources

An Optimized Hyperparameter Tuning for Improved Hate Speech Detection with Multilayer Perceptron

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Hate speech classification is a critical task in the domain of natural language processing, aiming to mitigate the negative impacts of harmful content on digital platforms.
Muhamad Ridwan, Ema Utami
doaj   +1 more source

Comparative Analysis of Hyperparameter Optimization Using Optuna and Hyperopt for Convolutional Neural Networks

Современные информационные технологии и IT-образование
The process of training a neural network model is controlled by selecting optimal hyperparameters, which have a significant impact on its quality and performance. This impact has been confirmed both theoretically and empirically by numerous studies.
Tatyana Samoilova
doaj   +1 more source

Advanced Sleep Disorder Classification: An ML-Based Study with Optuna for Model Optimization [PDF]

Hyperparameter optimization plays a crucial role in improving the performance of machine learning models, particularly in sleep disorder classification.
Andini, Nurul, Gaib, Amalan Fadil, Mahayudha, I Gusti Ngurah Bagus Ferry, Wijaya, Anggito Karta, Royan, Ando Zamhariro   +4 more
core   +4 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

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

AI-Driven Methane Emission Prediction in Rice Paddies: A Machine Learning and Explainability Framework

Methane
Rice cultivation accounts for roughly 10% of worldwide anthropogenic greenhouse gas emissions, making it a significant source of methane (CH4) Despite modest observational constraints, estimates of worldwide CH4 emissions from rice agriculture range from
Abira Sengupta, Fathima Nuzla Ismail, Shanika Amarasoma   +2 more
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Optimization of Scene and Material Parameters for the Generation of Synthetic Training Datasets for Machine Learning-Based Object Segmentation

Computers
Synthetic training data is often essential for neural-network-based segmentation when real datasets are difficult or impossible to obtain. Conventional synthetic data generation relies on manually selecting scene and material parameters. This can lead to
Malte Nagel, Kolja Hedrich, Nils Melchert, Lennart Hinz, Eduard Reithmeier   +4 more
doaj   +1 more source

Optuna-LightGBM : An Optuna hyperparameter optimization framework for the determination of solvent components in acid gas removal unit using LightGBM

Cleaner Engineering and Technology
Acid gas removal unit (AGRU) serves as an essential process in gas treatment, specifically designed to eliminate acid gases like hydrogen sulfide (H2S) and carbon dioxide (CO2) from natural gas. Absorption-based AGRU are extensively employing chemical solvents because of their strong performance and effectiveness.
Rafi Jusar Wishnuwardana, Madiah Binti Omar, Haslinda Binti Zabiri, Mochammad Faqih, Kishore Bingi, Rosdiazli Ibrahim   +5 more
openaire   +2 more sources