Project: Empathy Prediction using Eye-Tracking Data
This Python project aims to predict empathy levels in individuals based on eye-tracking data. The project utilizes machine learning techniques, including RandomForestRegressor with GroupKfold validation , to build a predictive model.
Getting Started
These instructions will guide you on how to set up the project on your local machine for development and testing purposes.
Prerequisites
To run this project, you'll need Python 3.x and the following libraries installed:
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn
- pickle
You can install these libraries using the following command:
pip install pandas numpy matplotlib seaborn scikit-learn pickle
Project Structure
The project is organized as follows:
- empathyhelper.py: Helper functions for data preprocessing, feature extraction, and model evaluation
- EyeT4Empathy-Dataset-analysis.ipynb: is the ML pipeline with Exploration and Example.
- Usage To run the project, simply execute the EyeT4Empathy-Dataset-analysis.ipynb. This will preprocess the data, extract relevant features, train the RandomForestRegressor model, and evaluate the model's performance using cross-validation.
Make sure to include all the necessary details to help users understand the project and its functionality.
Dataset Acknowledgements
The following data is used in this study. To utilize the dataset, simply download it and adjust the file paths according to your setup.
I would like to express my gratitude to the authors and contributors of the EyeT4Empathy dataset for making it publicly available. The dataset can be found at the following link:
Please cite the dataset using the following reference:
P. Lencastre, S. Bhurtel, A. Yazidi, S. Denysov, P. G. Lind, et al. EyeT4Empathy: Dataset of foraging for visual information, gaze typing and empathy assessment. Scientific Data, 9(1):1–8, 2022
```bibtex
@article{Lencastre2022,
author = {Lencastre, Pedro and Bhurtel, Sanchita and Yazidi, Anis and et al.},
title = {EyeT4Empathy: Dataset of foraging for visual information, gaze typing and empathy assessment},
journal = {Sci Data},
volume = {9},
pages = {752},
year = {2022},
doi = {10.1038/s41597-022-01862-w}
}
```