Results 41 to 50 of about 127,719 (261)

A Survey on Hyperparameters Optimization of Deep Learning for Time Series Classification

IEEE Access
Time series classification (TSC) is essential in various application domains to understand the system dynamics. The adoption of deep learning has advanced TSC, however its performance is sensitive to hyperparameters configuration.
Ayuningtyas Hari Fristiana, Syukron Abu Ishaq Alfarozi, Adhistya Erna Permanasari, Mahardhika Pratama, Sunu Wibirama   +4 more
doaj   +1 more source

An Intelligent Learning System Based on Random Search Algorithm and Optimized Random Forest Model for Improved Heart Disease Detection

IEEE Access, 2019
Heart failure is considered one of the leading cause of death around the world. The diagnosis of heart failure is a challenging task especially in under-developed and developing countries where there is a paucity of human experts and equipments.
Ashir Javeed, Shijie Zhou, Liao Yongjian, Iqbal Qasim, Adeeb Noor, Redhwan Nour   +5 more
doaj   +1 more source

A Hybrid Sparrow Search Algorithm of the Hyperparameter Optimization in Deep Learning

Mathematics, 2022
Deep learning has been widely used in different fields such as computer vision and speech processing. The performance of deep learning algorithms is greatly affected by their hyperparameters.
Yanyan Fan, Yu Zhang, Baosu Guo, Xiaoyuan Luo, Qingjin Peng, Zhenlin Jin   +5 more
doaj   +1 more source

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül, Neriman Sıla Koç, Berrak Itır Aylı   +2 more
wiley   +1 more source

Optimizing Deep Learning Models with Improved BWO for TEC Prediction

Biomimetics
The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. Recently, deep learning models have become increasingly popular in TEC prediction.
Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang   +6 more
doaj   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Tuning Bayesian optimization for materials synthesis: simulating two- and three-dimensional cases

Science and Technology of Advanced Materials: Methods, 2023
Compared to the optimization of a 1D synthesis parameter in materials synthesis, the optimization of multi-dimensional synthesis parameters is challenging for researchers.
Han Xu, Ryo Nakayama, Takefumi Kimura, Ryota Shimizu, Yasunobu Ando, Shigeru Kobayashi, Nobuaki Yasuo, Masakazu Sekijima, Taro Hitosugi   +8 more
doaj   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Design of adaptive soft sensor based on Bayesian optimization

Case Studies in Chemical and Environmental Engineering, 2022
When adaptive soft sensors are introduced to industrial plants, an appropriate combination of the type of adaptation mechanism, hyperparameters of the mechanism, regression model, and hyperparameters of the model must be selected for predictive soft ...
Shuto Yamakage, Hiromasa Kaneko
doaj   +1 more source

How priors of initial hyperparameters affect Gaussian process regression models

, 2017
The hyperparameters in Gaussian process regression (GPR) model with a specified kernel are often estimated from the data via the maximum marginal likelihood.
Chen, Zexun, Wang, Bo
core   +1 more source