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Welcome to the Causal Inference Pipeline wiki! On this page, you find a general overview of the project. Check out the sidebar to find out how to set it up or extend it with more features. The frontend repository can be found here.
The pipeline currently includes the following features, all of which are accessible via a REST API:
- Store causal inference ready datasets into our backend
- Set up causal inference experiments for different causal inference algorithms in R with different hyperparameter settings and dataset choice
- Run the experiments as jobs directly in our backend
- Manage all currently running jobs on the backend
- Deliver the results and meta information of past experiments
- Show distributions and perform interventions on results
- Annotate results with additional infromation
- Extend the pipeline with new algorithms in their own execution environments (e.g. C++)
The following image shows the holistic architecture as a FMC diagram:
You can download this image as signavio package and svg [here](https://github.com/hpi-epic/mpci/files/3013810/architecture.zip).
Controllers are called resources in our source code due to REST naming conventions, they can be found under master/resources.
Additionally, the data model can be seen as ER diagram:
You can download the ER diagram as .graphml file here.
All models are defined in the master/models directory.