IEEE

Feature Selection in Machine Learning for Wetland Water Level Prediction

Abstract: Water levels in wetlands are crucial for preserving the environment, maintaining biodiversity, controlling floods, and regulating water quality. Effective water level prediction in wetlands ...

Interview Kickstart's New Advanced Machine Learning and Agentic AI Program 2026 Helps Software Engineers Transition To Top ML and AI Roles

SANTA CLARA, CA - January 08, 2026 - - As organizations plan for 2026, a clear structural shift is emerging in how technical talent is valued and deployed. Amid this shift, Interview Kickstart has ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Frontiers

Enhanced SQL injection detection using chi-square feature selection and machine learning classifiers

Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...
IEEE

Hybrid Deep Machine Learning Feature Selection for High-Dimensional Cybersecurity Data

Abstract: The rapid increase in cyber threats has heightened the demand for Intrusion Detection Systems (IDS) that are both accurate and efficient. While deep learning models outperform traditional ...
Targeted Oncology

Machine Learning Model May Optimize Treatment Selection and Survival in HCC

The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...
AppleInsider

Apple Silicon machine learning code may become more easily portable to Nvidia hardware

A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA. Machine learning is costly to enter, in ...
Frontiers

Characterization and feature selection of volatile metabolites in Yangxian pigmented rice varieties through GC-MS and machine learning algorithms

Introduction: Pigmented rice is fascinated by consumers for its abundant phytochemicals and unique aroma. Methods: In this study, GC–MS-based metabolomics of Yangxian colored rice varieties were ...
marktechpost

Researchers at Stanford Introduces LLM-Lasso: A Novel Machine Learning Framework that Leverages Large Language Models (LLMs) to Guide Feature Selection in Lasso ℓ1 Regression

Feature selection plays a crucial role in statistical learning by helping models focus on the most relevant predictors while reducing complexity and enhancing interpretability. Lasso regression has ...