Abstract: By evaluating intricate datasets to maximize plant growth, boost yields, and advance sustainability, smart agriculture—powered by Random Forest machine learning—is transforming botany.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...

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 ...

One of the key issues faced by financial institutions is the prediction of loan default. Two machine learning methods, Random Forest and K-Nearest Neighbors (KNN), are tested in this study, using an ...