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pull_request_template.md

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Competition Checklist:

  • title of this PR is meaningful, i.e. "method X for comp"
  • A folder has been added to submission/ with a meaningful name corresponding to your method name.
  • The added folder includes these elements:

    • metadata.yml (required): A file describing your submission, following the descriptions in example/metadata.yml.

    • regressor.py (required): a Python file that defines your method, named appropriately. See submission/feat-example/regressor.py for complete documentation. It contains:

      • est: a sklearn-compatible Regressor object.
      • model(est, X=None): a function that returns a sympy-compatible string specifying the final model. It can optionally take the training data as an input argument. See guidance below.
      • eval_kwargs (optional): a dictionary that can specify method-specific arguments to evaluate_model.py.

    • LICENSE (optional) A license file

    • environment.yml (optional): a conda environment file that specifies dependencies for your submission.

    • install.sh (optional): a bash script that installs your method.

    • additional files (optional): you may include a folder containing the code for your method in the submission.

I have verified that:

  • install scripts do not require sudo permissions.
  • if pulled remotely, the source code is a fixed version (i.e., rerunning install.sh shouldn't pulll a different version of the code when run multiple times.)

Refer to the competition guide if you are unsure about any steps. If you don't find an answer, ping us!