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Further doc updates #54
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CI tests are failing due to unrelated issues as documented in #55. Tests and linting pass on my machine. This PR now involves:
Most comments in #53 would involve substantial actual code changes, so should probably be addressed separately |
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This is great Jack! You've put in a lot of great work!
I only have one comment in this review about cv
. Otherwise some things to consider:
- Include the README in the docs front page (as we did in aboleth) so users are given a nicer front page other than just the API reference
- host the docs on readthedocs, and make a hook in the CI that rebuilds these docs and uploads it to readthedocs
Otherwise I'll leave it to Simon and Al :-)
README.md
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@@ -103,7 +103,8 @@ pieval = PermutationImportanceEvaluator(n_repeats=5) | |||
# Bootstrap sample the data, re-fitting and re-evaluating the model each time. | |||
# This will run the GridSearchCV estimator, so thereby performing model | |||
# selection within each bootstrap sample. | |||
bootstrap_model(best_model, X, Y, [pdeval, pieval], replications=30) | |||
# n_jobs=-1 parallelises the bootstrapping to use all cores. |
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nice
cinspect/model_evaluation.py
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evaluators : Sequence[Evaluator] | ||
A list of evaluators. | ||
cv : Union[int, BaseCrossValidator], optional | ||
The cross validation strategy, by default KFold(n_splits=5) |
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It may be worth mentioning that if this is of type int
, it results in KFold(n_splits=cv)
as per scitkit-learn's interface
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This PR will contain additional documentation updates and address comments from #53