guischmitd / kddbr-2022

KDDBR-2022 Submission Repo

Solution for the 2022 KDDBR kaggle competition.

Author: Guilherme Baraúna

https://www.kaggle.com/guischmitd

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Running the code

To run the solution, follow these steps:

1. Download the competition data from kaggle and unzip it into data/raw to replicate the following structure:

data
├── feats
├── models
├── processed
├── raw
│   ├── test
│   │   └── test
│   └── train
│       └── train
└── subs

2. Create a virtual environment, activate it and install dependencies:

# On Linux/MacOS
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# On Windows (Git Bash or PowerShell)
python3 -m venv .venv
source .venv/Scripts/activate # Or activate.ps1
pip install -r requirements.txt

3. Run all cells on kddbr/final_submission.ipynb. Each section of the notebook will generate specific files required for next cells.

Note: Since some of the processes take some time, files will be cached by default and accessed in case they are found. You can skip loading the cached data by setting FORCE_RUN=True on specific cells.

4. Models will be saved under data/models as joblib pickled files. Submissions in the standard competition format (.csv) will be sabe under data/subs