# Title

[Intro]

This repository is organized as follows:
* [EDA](./EDA): Exploring data, handling missing values, analyzing variable distribution, filtering data, feature selection, encoding variables, and performing correlation analysis.
* [gen_train_data](./gen_train_data): Generating training and testing datasets [wait for final approach TBC].
* [model_selection](./model_selection): Tuning models, generating metrics from cross-validation and testing, and selecting final models.
    * [hyperparam_tuning.py](./model_selection/hyperparam_tuning.py): Tunes models through a random search of hyperparameters.
    * [cv_metric_gen.py](./model_selection/cv_metric_gen.py): Generates cross-validation metrics and plots for the tuned models.
    * [cv_metrics_distr.py](./model_selection/cv_metrics_distr.py): 
* [explainability](./explicability): SHAP explainability analysis, comparing pre- and post-pandemic groups.

[Outro]