Abstract: Multi-class classification is a current research area within machine learning, aimed at solving problems where input data is categorized into more than two classes. The dataset is in English ...

SHENZHEN, China, Nov. 15, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Multi-class network intrusion detection using CatBoost with GPU/CPU support, handling highly imbalanced datasets. Includes stratified downsampling, K-Fold cross-validation, and explainable AI with ...

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.

Identify algorithmic structures in source code using Abstract Syntax Trees (ASTs) and a CodeBERTa-based classifier. Combines syntactic analysis with transformer embeddings for structure classification ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

Lorich uses her obsessive personality for good by learning way too much about video game lore. Need someone to break a story down? She's your gal. You know her, you love her, she's the worst Sage main ...

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...