Open Access Government

Basic machine learning with lessR : Easy, simple, and free

David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...
Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
MIT Technology Review

Teaching AI to run with the turbines

As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...

Retailers are calling on AI to stop customer return fraud

Retailers are implementing AI through software companies like Happy Returns and Narvar to detect return fraud and issue ...
Virtualization Review

Running AI Locally, Part 2: From VMware Context to Hands-On Tools

Tom Fenton moves from local AI concepts to hands-on tools for matching LLMs to hardware, running local chatbots with Ollama and benchmarking AI performance.
Communications of the ACM

Teaching LLMs to Give Better Answers

As a result, researchers are exploring ways to embed better logic into AI. The goal isn’t so much to make LLMs smarter; it’s ...
IEEE

Random Interaction Forest (RIF)–A Novel Machine Learning Strategy Accounting for Feature Interaction

Abstract: If an interaction exists in medical and health sciences, a proper statistical approach is required to avoid an erroneous conclusion. For example, different genders may introduce modified ...
Investopedia

Predictive Modeling: Techniques, Uses, and Key Takeaways

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Jared Ecker is a researcher and fact-checker ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Frontiers

Development of an interpretable machine learning model for predicting sarcopenia in patients undergoing maintenance hemodialysis

Sarcopenia has a high incidence among patients undergoing maintenance hemodialysis (MHD), significantly increasing the risk of falls, fractures, and mortality. Traditional diagnostic methods, however, ...
Frontiers

Expectation-maximization alternating least squares for tensor network logistic regression

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
IEEE

Generating Adversarial Malware Examples Against Multiple Machine Learning Detectors

Abstract: Malware poses a significant threat to network and information system security, particularly in industrial Internet of Things (IIoT) environments, where embedded systems and edge devices ...