i am learning how to publish stuff , will be deleted soon

This project applies a range of tree-based machine learning models, including Decision Trees, Random Forest, Bagged Trees, and Boosted Trees, to predict loan approval outcomes. By leveraging hyperparameter tuning and cross-validation techniques, this analysis optimizes model performance on a loans dataset to identify patterns and improve decision-making accuracy.

The Takhini River near Whitehorse (09AC001) will be used as a case study to demonstrate a standard FFA using annual maximum flows.