This is the official repository, containing code and data for the paper:
T. Thomas, D. Straub, F. Tatai, M. Shene, T. Tosik, K. Kersting, C. A. Rothkopf. Modelling dataset bias in machine-learned theories of economic decision-making. Nature Human Behaviour (2024)
https://doi.org/10.1038/s41562-023-01784-6.
All three datasets, i.e. CPC15, CPC18 and choices13k used in this study have been publicly avialable. Aggregate versions without individual data and with additional features and some utility columns are stored in the data folder.
The Analysis notebook shows how to reproduce many of the plots and analysis done in the paper.
Pretrained models under the name that they were shown in Table 1 in the paper are stored in the models folder.
The models notebook gives simple examples how to load, save and train the NN models discussed in the paper.
The underlying source code for them is in the src folder.
To use the notebooks and reproduce our results, install the conda environment, using
conda env create -f environment.yml
conda activate DecisionMaking
Thomas, T., Straub, D., Tatai, F. et al. Modelling dataset bias in machine-learned theories of economic decision-making. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-023-01784-6