Current priorities are on the Board 🎬.
Prediction of type 2 diabetes among patients with visits to psychiatric hospital departments.
This is a set of modules used for some of the projects' model training. You need project-specific code to use these modules. To get started with that, see template-model-training.
pip install --src ./src -e git+https://github.com/Aarhus-Psychiatry-Research/psycop-model-training#egg=psycop_model_training
In general, model evaluations are added as their own file in
src > psycop_model_training > model_eval > base_artifacts > plots/tables
To make sure they run every time, also add them to base_artifact_generator.py
.
However, when developing, it's much faster to develop on a synthetic dataset.
To do that:
Work locally
- Write your plot function in an appropriate file in the
src > psycop_model_training > model_eval > base_artifacts > plots/tables
directory. - Test the plot on synthetic prediction data. Write a test in
tests > model_evaluation > test_name_of_your_plot.py
. Use the other visualization tests as a guide.
Work remotely
- When you're happy with the plot, test it on real data on Overtaci. To do this, go to Overtaci and replace the path in your test script with some real model predictions with metadata.