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update README with current TODOs
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MaximilianFranz committed Nov 19, 2019
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# Further Work
Some steps to continue the work on this project would be
- Implement a fully parametric DGP, following the dimensions roughly outlined in Chapter 4 of my thesis
Some steps to continue the work on this project would be:
- Allow to use Confidence Intervals in the learners (see `causalml`, for example) and in the evaluation
- Implement a fully parametric DGP, following the dimensions roughly outlined in Chapter 4 of the thesis
- Rewrite the plot functions in `utils.py` to simply take `DataProvider` as inputs and handle the internals within
the functions.
- Implement within-sample and out-of-sample evaluation (switch between the two) as proposed in [this paper](https://arxiv.org/pdf/1606.03976.pdf).
- Implement a run-checker that ensures that all methods fit on the data and/or that no complications arise,
before expensive computation is started.
(e.g. requested size is to big for given DataProvider)
- Enable evaluation without `sacred` logging, only storing results.
- Ensure train/test split can be requested for all DataProviders
- Obviously, add more methods and reference datasets
- Implement experiment as a module, which is given methods, data and settings of the experiments and returns the full
- add the final bachelor thesis as pdf under `docs` and reference it in Sphinx
- Separate Loggin/Writing stuff from the actual calculation of metrics in metrics.py (single level of responsibility)
- Obviously, add more methods and reference datasets ;)
- use Sphinx (checkout `docs` folder) to create command reference and some explanations.
- add some example notebooks in the notebooks folder
- add some example notebooks in the `notebooks` folder of experiments and parameter studies
- Check licences of third-party methods and add and note them accordingly. Within the __init__.py of the subpackage
add a docstring and state the licences and the original authors.

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