Lake County Record-Bee

Machine learning helps wildfire forecasts

With peak wildfire season underway in California, PG & E’s Chief Meteorologist Scott Stenfel held a virtual Wildfire Season ...
Aerospace and Mechanical Insider on MSN

AI and machine learning transform materials testing

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...
Hosted on MSN

Giant tree clearing machine working deep in the forest

A massive John Deere forestry machine powers through dense woodland while clearing trees, crushing brush, and tearing through rough terrain. The giant heavy equipment showcases incredible strength, ...
Visual Studio Magazine

Decision Tree Regression from Scratch Using JavaScript

Decision tree regression is a fundamental machine learning technique to predict a single numeric value. A decision tree regression system incorporates a set of virtual if-then rules to make a ...
IEEE

Fuzzy Decision Trees for Small Data Analysis: Interpretable Learning From Limited Samples

Abstract: Machine learning with small datasets presents well-known challenges, including overfitting and unreliable estimates. While fuzzy logic provides a framework for handling uncertainty, existing ...
The New York Times

Starting at Harvard and Falling for Your First Tree

A freshman seminar encourages students to behave differently in the world and feel more passionately about biodiversity. Each Harvard University freshman in the “Tree” seminar must choose a single ...
Frontiers

Clinical decision system for renal cell carcinoma integrating interpretable machine learning algorithms

Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and improve prognosis ...
The Lancet

Oesophageal cancer multi-disciplinary tool: a co-designed, externally validated, machine learning tool for oesophageal cancer decision making

These authors are jointly share Last Author for this manuscript. Clinicopathological data collected from 1931 patients between 4th September 2009, and 8th November 2022 were used to test and validate ...
Scientific Research Publishing

Mohammadagha, M. (2025) Hyperparameter Optimization Strategies for Tree-Based Machine Learning Models Prediction: A Comparative Study of Ada-Boost, Decision Trees, and Random ...

ABSTRACT: This study presents a comprehensive and interpretable machine learning pipeline for predicting treatment resistance in psychiatric disorders using synthetically generated, multimodal data.
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
GitHub

Example Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using Amazon SageMaker.

These example notebooks are automatically loaded into SageMaker Notebook Instances. They can be accessed by clicking on the SageMaker Examples tab in Jupyter or the SageMaker logo in JupyterLab.