InfoQ

Fraud Detection Using Random Forest, Neural Autoencoder, and Isolation Forest Techniques

Any supervised machine learning algorithm could work. For demonstration purposes, we have chosen a random forest with 100 trees, all trained up to a depth of ten levels and with a maximum of three ...
ascopubs.org

Using machine learning to predict mortality in older patients with cancer: Decision tree and random forest analyses from the ELCAPA and ONCODAGE prospective cohorts.

Prediction of treatment (tx)-induced fatigue in breast cancer (BC) patients (pts) using machine learning on genome-wide association (GWAS) data in the prospective CANTO cohort. This is an ASCO Meeting ...
Hackaday

Training Bats In The Random Forest With The Confusion Matrix

When exploring the realm of Machine Learning, it’s always nice to have some real and interesting data to work with. That’s where the bats come in – they’re fascinating animals that emit very ...
The Conversation

This March Madness, we’re using machine learning to predict upsets

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...