IEEE

Collating Random Forest Classifier and Artificial Neural Networks for the Risk Detection of Maternal Health

Abstract: This paper compares the performance of ANN models to Random Forests on benchmarking a test dataset against the risk levels of maternal health as low, mid, or high. The features considered ...
IEEE

Utilizing Random Forests for High-Accuracy Classification in Medical Diagnostics

Abstract: In recent years, medical diagnostics has increasingly relied on machine learning techniques to improve accuracy and efficiency. Among these, the Random Forest algorithm has emerged as a ...
GitHub

AI Firewall Classification System

The AI Firewall Classification System is a machine learning-based tool that automatically detects and classifies network firewall types based on their behavioral characteristics. The system analyzes ...
Frontiers

Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China

Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level ...