954 prediction explanations doc #981
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…elines/explanations.
…es to _explain_prediction.
…ing section on SHAP to model_understanding tutorial.
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Coverage 99.85% 99.85%
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Files 178 179 +1
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+ Hits 9269 9270 +1
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freddyaboulton
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dsherry and
jeremyliweishih
and removed request for
dsherry and
jeremyliweishih
angela97lin
approved these changes
Jul 27, 2020
|
@angela97lin Thanks! Good point, I'll delete in this PR! |
dsherry
reviewed
Jul 28, 2020
| "\n", | ||
| "In the example below, we explain the prediction for the third data point in the data set. We see that the `worst concave points` feature increased the estimated probability that the tumor is malignant by 20% while the `worst radius` feature decreased the probability the tumor is malignant by 5%.\n", | ||
| "\n", | ||
| "The interpretation of the table is the same for regression problems - but the SHAP value now corresponds to the change in the estimated value of the dependent variable rather than a change in probability. For multiclass classification problems, a table will be output for each possible class." |
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@freddyaboulton I just checked this out. This looks great! My only thought was this paragraph could go after the example since its not directly connected to the example.
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Pull Request Description
Fixes #954 by adding
explain_predictionto the api reference and by adding example usage to the Model Understanding tutorial in the user guide.Docs Change
After creating the pull request: in order to pass the release_notes_updated check you will need to update the "Future Release" section of
docs/source/release_notes.rstto include this pull request by adding :pr:123.