Harvard Business Review

Decision Trees for Decision-Making

Here is a [recently developed] tool for analyzing the choices, risks, objectives, monetary gains, and information needs ...
Scientific Research Publishing

A New Method to Predict the Mechanical Behavior for a Family of Composite Materials ()

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...
IEEE

Decision Trees in Federated Learning: Current State and Future Opportunities

Abstract: Federated learning (FL) is a distributed machine learning technique that enables multiple decentralized clients to develop a model collaboratively without exchanging their local data.

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...

MachineLearningLM Equips Large Models with a 'Machine Learning Engine' for Context Learning

Despite large language models (LLMs) possessing extensive world knowledge and strong reasoning capabilities, they are widely regarded as excellent few-shot learners; however, they still exhibit ...
C&EN

Machine-Learning Potential Molecular Dynamics Reveals the Critical Role of Flexibility in Solid–Liquid Nanofluidic Friction

Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, ...
IEEE

An Adaptive Framework for Low-Rate DDoS Detection in Cloud Environments Using Decision Tree Machine Learning Algorithm

Abstract: An adaptive detection framework to identify low-rate Distributed Denial of Service (DDoS) attacks in cloud environments. Leveraging the Decision Tree machine learning algorithm, the ...
Frontiers

Real-world data-driven early warning system for risk-stratified liver injury in hospitalized COVID-19 patients—Machine learning models for clinical decision support

Objective: To develop and validate a real-world evidence-driven early warning system for the risk-stratified prediction of coronavirus disease 2019 (COVID-19)-associated hepatic dysfunction in ...