Results 131 to 140 of about 6,929,542 (320)
Given that the decision tree C4.5 algorithm has outstanding performance in prediction accuracy on medical datasets and is highly interpretable, this paper carries out an optimization study on the selection of hyperparameters of the algorithm in order to ...
Yiyan Zhang, Yi Xin, Qin Li
doaj +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
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
Optimisasi Hyperparameter BiLSTM Menggunakan Bayesian Optimization untuk Prediksi Harga Saham
The accuracy of deep learning models in predicting dynamic and non-linear stock market data highly depends on selecting optimal hyperparameters. However, finding optimal hyperparameters can be costly in terms of the model's objective function, as it ...
Fandi Presly Simamora +2 more
doaj +1 more source
Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini +7 more
wiley +1 more source
Federated Learning is transforming electrical load forecasting by enabling Artificial Intelligence (AI) models to be trained directly on household edge devices.
Liana Toderean +6 more
doaj +1 more source
Initializing Bayesian Hyperparameter Optimization via Meta-Learning
Model selection and hyperparameter optimization is crucial in applying machine learning to a novel dataset. Recently, a subcommunity of machine learning has focused on solving this problem with Sequential Model-based Bayesian Optimization (SMBO ...
Hutter, Frank +2 more
core +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength
This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models.
Jeonghyun Kim, Donwoo Lee
doaj +1 more source
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source
An Optimized Hyperparameter Tuning for Improved Hate Speech Detection with Multilayer Perceptron
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

