insideHPC

TECH TIP: An Introduction to Random Forests

Random Forests Co-Developer Dr. Adele Cutler visited Salford Systems in San Diego, CA. While she was visiting, she gave the staff a few quick presentations and interviews related to the popular Random ...

Machine learning approach simulates geochemical element concentrations in rocks and stream sediments

To address this issue, the researchers applied the Random Forest machine learning model, which enables the simulation of ...
Healio

MRI-based clinical prediction model identified risk factors for patellar instability

Please provide your email address to receive an email when new articles are posted on . The Insall-Salvati ratio, tibial tubercle-trochlear groove distance and trochlear depth had the greatest ...
Risk.net

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...
EurekAlert!

Strategic reuse of rapid antigen tests for coagulation status assessment: an integrated machine learning approach

• Repurposed COVID-19 RATs provide an ideal platform for observing differences in blood coagulability. • Random Forest image classification algorithms can facilitate rapid coagulation status ...
Visual Studio Magazine

Random Forest Regression and Bagging Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...