Added PPT

Updating GitHub with final processing script

Completed SHAP analysis for Naive Bayes (KernelExplainer) and Random Forest Classifier (TreeExplainer)

Made some changes to prepare to use SHAP on final two models

Made small changes to the files as I updated my powerpoint documenting my methodology

Formated the testing data and tested it against the two final models

Final models are ready to be tested against final test data. Next steps are to prepare the test data

Picked final models for each dataset (tomek, tomek+random undersampling) after tuning them using optuna. Gaussian Naive Bayes worked best for the tomek data, and Random Forest Classifier worked best for the tomek+rus data.

Completed run through of models on the two datasets (tomek, tomek+rus), and now we are ready for optuna

Finished processing data, now we can move to the machine learning portion

Ready to run Tomek Links on data

Almost done transforming categorical data

Found transformation method that works for numerical data

Started data preprocessing, and setup code to look at different data transformations

Saved data to be preprocessed