Utilizing Decision Tree algorithms to predict the hardness of the mineral on the Mohs scale of hardness based on the properties given from the dataset.
The following .ipynb file focuses mainly on the XGBoost decision tree alogrithm and an advanced hyperparameter tuning method: gridsearchCV. trimming and cleaning up the dataset scraped.
The file only implements the 80/20 split to gauge how overfitted or underfitted the model is to the dataset.
The code has been taken from my final submission to a Kaggle Competition that i had competed in. link: https://www.kaggle.com/competitions/round-2-nexus-recruitment/overview