Closed bammari closed 9 months ago
Patch coverage: 98.94%
and project coverage change: +0.54%
:tada:
Comparison is base (
dcca13c
) 95.40% compared to head (349dfa0
) 95.95%.
:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.
Please also add a description of the new Jupyter notebook in docs/notebooks.rst
Going through minor things and want to make sure @bammari gets credit for this work. Would you please also add to this PR:
In README.rst
In the new notebook, please add the C&CE paper as a reference. As an example of how to do this, see bo_with_trees.ipynb
Going through minor things and want to make sure @bammari gets credit for this work. Would you please also add to this PR:
In README.rst
- Please add a reference to the Computers & Chemical Engineering paper. State that if anyone uses the linear tree implementation, they should cite the C&CE paper.
- Please add @bammari to the list of contributors at the bottom and state his funding.
In the new notebook, please add the C&CE paper as a reference. As an example of how to do this, see bo_with_trees.ipynb
Added reference to CACE paper in both the notebook and Readme.rst. I also updated the OMLT paper reference from Arxiv to Journal of ML Research in README.rst. In addition, added contribution statement - Bashar
This PR now allows users to embed linear model decision trees (trained with the linear-tree package https://github.com/cerlymarco/linear-tree) within OMLT. We include several univariate and bivariate tests to ensure the several implemented formulations are functional. Furthermore, this PR includes a preliminary Jupyter notebook that shows how to embed these linear model decision trees. using OMLT
In addition to this implementation, this PR also rewrites the way scaled_input_bounds are defined within the _setup_scaled_inputs_and_outputs function in formulation.py. Specifically, we pass a dictionary of tuples containing lower and upper bounds rather than constructing a bounds rule. test_maxpool_FullSpaceNNFormulation was failing without this change.
Legal Acknowledgement\ By contributing to this software project, I agree my contributions are submitted under the BSD license. I represent I am authorized to make the contributions and grant the license. If my employer has rights to intellectual property that includes these contributions, I represent that I have received permission to make contributions and grant the required license on behalf of that employer.