Health Food Symmetry leads way in new gut-boosting fibre classification

Australian food scientists are working to overhaul how dietary fibre is classified beyond soluble and insoluble to better inform nutrition choices and support development of functional foods in a ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
GitHub

[QUESTION] Determine whether distillation is appropriate for task

Thank you for the awesome library. I am trying to determine whether a specific task would be a good fit for distillation. I am working on training a distilled binary classification model to determine ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
eLife

Fast evolutionary turnover and overlapping variances of sex-biased gene expression patterns defy a simple binary sex classification of somatic tissues

This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.
C&EN

Optimizing Multi-Task Learning with Evolutionary Relatedness Metrics for Enhanced QSAR-Based Natural Product Activity Prediction

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A few public databases provide biological activity data for ...
IEEE

Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning

Abstract: In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to ...
Frontiers

High-accuracy lung sound classification for healthy versus unhealthy diagnosis using artificial neural network

In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing pulmonary disease ...