Update EvalML section of tutorials #198
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Note - I did get slightly different results from the original tut
around feature importance, and prediction results. But, unless I
missed a new randomness param, I think this may be because of
underlying changes in the evalml package. Not sure though.
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wood work is a core dependency of evalml
this is so the build process can automatically run the notebooks
Codecov Report
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happy to squash or rebase if y'all do that, too |
flowersw
changed the title
flowersw
changed the title
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Fixes #197 |
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Ok, I think we're good. I'm assuming you'll merge it, as I don't seem to be able to. Thanks |
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Thanks @flowersw ! Yes, the difference in output you saw is due to updates we've made to EvalML, including adding more models and fixing bugs. |
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This simply updates the evalml section of the tutorial notebooks in the documentation, to be up to date with evalml 0.17, and pins evalml and woodwork higher and gte in the docs requirements.txt file.
I did want to note that in case these tutorials are benchmark or meant to be exactly reproducible in some way, I noticed a few slight differences in the output of the models, e.g. slightly different evaluation accuracy, slightly different feature importances, etc.. Unless I'm missing a new "randomness" parameter, I would guess that's due to the underlying changes in evalml, but am not sure.