This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
AI Steam updates AI disclosure form to specify that it's focused on AI-generated content that is 'consumed by players,' not efficiency tools used behind the scenes AI Stellar Blade's director says AI ...
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...