dzhen19 / cs91.3 Goto Github PK

Files in this repo are split up between classification / regression task.

1. Install all packages in requirements.txt by running pip3 install -r requirements.txt

1. Download the zipped data from this link: https://drive.google.com/file/d/1TMpNu_hQVGZqOlziCUBbJCXA8e6ER0wD/view?usp=sharing
2. Unzipping the file should yield a folder named prepared_data/ containing multiple files ending with .npz.
3. Drag the prepared_data/ folder into the data/ folder in this repo.
4. After installing all dependencies, run main_classification.py. Results are both printed to stdout and saved in classification_results.csv.

1. Download the Position_task_with_dots_synchronised_min.npz (https://osf.io/ge87t/) from OSFHome (https://osf.io/ktv7m/). Move this file directly into the data/ folder.
2. For the regression tasks, repro using regression_notebook.ipynb.
3. To open notebooks, type "jupyter-notebook" (without the quotations) in your terminal, then copy paste the given urls into a browser.
4. Click "Run All" for both notebooks in your Jupyter notebook UI.
5. The notebook may take 30 minutes to an hour to run