Hyperparameter results of various sample sizes and sampling schemes under random forests

This study assesses the "effects of various sampling schemes on spatially autocorrelated data using tree-based machine learning algorithms". It will serve as a guideline in using sampling schemes and modelling techniques in the presence of spatial autocorrelation. This repository is the final iteration of the thesis "Assessing the Effects of Various Sampling Schemes on Tree-Based Machine Learning Algorithms" by Edward Baleni and Sachinn Phalad, supervised by Sebnem Er, Sulaiman Sulau and Inger Fabris-Rotelli.