UnitX Launches The World's Fastest to Deploy AI Smart Camera to Bridge the Manufacturing Vision Gap

Ecosystem-agnostic edge camera deploys in 1 minute and delivers enterprise AI capabilities at cost of a basic vision sensor, ...
IEEE

Multiclass Classification on High Dimension and Low Sample Size Data Using Genetic Programming

Abstract: Multiclass classification is one of the most fundamental tasks in data mining. However, traditional data mining methods rely on the model assumption, they generally can suffer from the ...
InfoWorld

Using AI-powered email classification to accelerate help desk responses

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...
Scientific Research Publishing

Research on Fault Detection and Classification of Industrial Equipment Based on Machine Learning ()

In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...
IEEE

A Multiclass Graph Embedding Matrix Classification Method for Roller Bearing State Identification Under Limited Sample

Abstract: Support matrix machine (SMM) based methods have revolutionized the field of state identification by effectively mining correlations between fault features. However, some flaws limit its ...
Nature

A multi-classification deep neural network for cancer type identification from high-dimension, small-sample and imbalanced gene microarray data

Gene microarray technology provides an efficient way to diagnose cancer. However, microarray gene expression data face the challenges of high-dimension, small-sample, and multi-class imbalance. The ...
Frontiers

A review on over-sampling techniques in classification of multi-class imbalanced datasets: insights for medical problems

There has been growing attention to multi-class classification problems, particularly those challenges of imbalanced class distributions. To address these challenges, various strategies, including ...
Nature

Classification performance assessment for imbalanced multiclass data

The evaluation of diagnostic systems is pivotal for ensuring the deployment of high-quality solutions, especially given the pronounced context-sensitivity of certain systems, particularly in fields ...
Visual Studio Magazine

Multi-Class Classification Using LightGBM

Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...
Frontiers

Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learning

Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or more classes. Here we ...