Fort Bragg Advocate-News

Machine learning helps wildfire forecasts

With peak wildfire season underway in California, PG & E’s Chief Meteorologist Scott Stenfel held a virtual Wildfire Season ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Investopedia

Decision Trees in Finance: A Tool for Analyzing Risks and Outcomes

Arthur Pinkasovitch, CFA, has worked 5+ years as a financial analyst. He is an associate director at ATB Financial. David Kindness is a Certified Public Accountant (CPA) and an expert in the fields of ...
Hacker

How To Plot A Decision Boundary For Machine Learning Algorithms in Python

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...
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 ...
C&EN

Modified Decision Tree with Custom Splitting Logic Improves Generalization across Multiple Brains’ Proteomic Data Sets of Alzheimer’s Disease

V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia ...
GitHub

GBDT-MO: Gradient Boosted Decision Tree for Multiple Outputs

Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...
VentureBeat

Improving decision-making in LLMs: Two contemporary approaches

Emergent large language models (LLMs) such as OpenAI’s ChatGPT (particularly its latest iteration, GPT-4), Claude AI and Gemini have demonstrated limited decision-making. In this article, we’ll ...
EurekAlert!

Inexpensive water-treatment monitoring process powered by machine learning

Small, rural drinking water treatment (DWT) plants typically use only chlorine to implement the disinfection process. For these plants, free chlorine residual (FCR) serves as a key performance measure ...
Visual Studio Magazine

Decision Tree Regression from Scratch Using C#

Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...
IEEE

Differentiable-Decision-Tree-Based Neural Turing Machine Model Integrated Into FDTD for Implementing EM Problems

Abstract: As known to all, problems consume more and more computational resources, for example, memory and time, with the gradual enhancements of both the size of the physical domain and complexity in ...
Frontiers

Editorial: Driving Innovation in Organic Optoelectronic Materials With Physics-Based and Machine-Learning De Novo Methods

Organic materials are a rapidly evolving class of compounds for applications in current and future optoelectronic devices. Contributing to the swift pace of discovery of new materials are ...