- Created a new Jupyter notebook `EDA_Decision_Tree.ipynb` for exploratory data analysis and decision tree classification using the biologically selected dataset.
- Developed a Python script `make_decision_tree_notebook.py` to automate the creation of the decision tree notebook, including data preparation, model training, evaluation, and visualization steps.
- Implemented iterative tuning of the decision tree model with cross-validation and hyperparameter search for improved performance and interpretability.
rpotter6298