Displaying the top_k features with largest shap value magnitudes #1374
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## main #1374 +/- ##
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- Coverage 100.0% 100.0% -0.0%
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Files 213 213
Lines 13942 13940 -2
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freddyaboulton
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| @@ -452,7 +453,7 @@ | |||
| "name": "python", | |||
| "nbconvert_exporter": "python", | |||
| "pygments_lexer": "ipython3", | |||
| "version": "3.7.5" | |||
| "version": "3.8.3" | |||
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this doesnt need to be changed
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| # Sort the features s.t the top_k w the largest shap values are the firt | ||
| # top_k elements | ||
| tuples = sorted(tuples, key=_neg_shap_value_magnitude) |
| def _neg_shap_value_magnitude(shap_tuple): | ||
| return -abs(shap_tuple[0]) | ||
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| # Sort the features s.t the top_k w the largest shap values are the firt |
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Typo? the top_k w the largest shap values are the firt --> the top_k with the largest shap values are the first
| features_to_display = reversed(tuples) | ||
| else: | ||
| features_to_display = tuples[-top_k:][::-1] + tuples[:top_k][::-1] | ||
| def _neg_shap_value_magnitude(shap_tuple): |
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Is this done strictly to sort the features w/ largest SHAP values first? If so, maybe we don't need this, and can use:
tuples = sorted(tuples, key=lambda x: x[0], reverse=True)
(Syntax not guaranteed ahaha)
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I originally went with a def instead of a lambda because I thought our linting prevented lambdas but it prevents assigning to a lambda, not all lambdas.
So this is not allowed:
first_value_abs = lambda x: abs(x[0])
tuples = sorted(tuples, key=first_value, reverse=True)But your suggestion is allowed! I guess the intention is to keep lambdas anonymous which makes sense.
TIL something hehe. I'll update to use the in-line lambda.
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| @@ -5,6 +5,7 @@ Release Notes | |||
| * Enhancements | |||
| * Added ability to freeze hyperparameters for AutoMLSearch :pr:`1284` | |||
| * Added the index id to the ``explain_predictions_best_worst`` output to help users identify which rows in their data are included :pr:`1365` | |||
| * The top_k features displayed in ``explain_predictions_*`` functions are now determined by the magnitude of shap values as opposed to the ``top_k`` largest and smallest shap values. :pr:`1374` | |||
| .. warning:: | ||
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| **Breaking Changes** | ||
| * The ``top_k`` and ``top_k_features`` parameters in ``explain_predictions_*`` functions now return ``k`` features as opposed to ``2 * k`` features :pr:`1374` |
Pull Request Description
Fixes #1360
FYI @RezaAkhtar
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.