@@ -20,7 +20,7 @@ This repository is organized as follows:
...
@@ -20,7 +20,7 @@ This repository is organized as follows:
*[output](./EDA/output): Plots about feature distributions, correlations and importance.
*[output](./EDA/output): Plots about feature distributions, correlations and importance.
*[EDA.ipynb](./EDA/EDA.ipynb): Exploring and filtering data, handling missing values, encoding variables, building the final pre- and post- pandemic datasets, and generating plots for feature distributions, correlations and importance.
*[EDA.ipynb](./EDA/EDA.ipynb): Exploring and filtering data, handling missing values, encoding variables, building the final pre- and post- pandemic datasets, and generating plots for feature distributions, correlations and importance.
*[gen_train_data](./gen_train_data):
*[gen_train_data](./gen_train_data):
*[gen_train_data.ipynb](./gen_train_data/gen_train_data.ipynb): Generating training and testing datasets.
*[gen_train_data.ipynb](./gen_train_data/gen_train_data.ipynb): Generating training and testing datasets for each of the pipelines.
*[model_selection](./model_selection):
*[model_selection](./model_selection):
*[hyperparam_tuning.py](./model_selection/hyperparam_tuning.py): Tuning models through a random search of hyperparameters.
*[hyperparam_tuning.py](./model_selection/hyperparam_tuning.py): Tuning models through a random search of hyperparameters.
*[cv_metric_gen.py](./model_selection/cv_metric_gen.py): Generating cross-validation metrics and plots for each of the tuned models.
*[cv_metric_gen.py](./model_selection/cv_metric_gen.py): Generating cross-validation metrics and plots for each of the tuned models.