Find rows near the decision boundary #2908
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@@ Coverage Diff @@
## main #2908 +/- ##
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+ Coverage 99.7% 99.7% +0.1%
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Files 302 302
Lines 28433 28587 +154
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+ Hits 28340 28494 +154
Misses 93 93
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bchen1116
requested review from
chukarsten,
dsherry,
freddyaboulton,
angela97lin,
christopherbunn,
jeremyliweishih and
ParthivNaresh
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@bchen1116 Thanks for this! I left some minor comments for improving the implementation and tests. I am only "blocking" because I would like to discuss whether "epsilon" is a more useful parameter than "num_rows". I think it's confusing we return all rows by default.
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| assert all(vals.values == expected_vals) | ||
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| if types == "all": |
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Isn't this check redundant?
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This is just double-checking that we can exclude passing in y and still get the same results
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Thanks for explaining!
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Super thorough testing. Some of the tests took me a minute to realize what exactly was being tested. Perhaps this could be remedied with maybe more specific names for the tests? I feel like test_rows_of_interest_threshold was the one that I spent the most time on. Anyway, nothing blocking. Just food for thought.
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| if threshold is not None and (threshold < 0 or threshold > 1): | ||
| raise ValueError( | ||
| "Provided threshold {} must be between [0, 1]".format(threshold) |
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nit: hard brackets is for inclusive, might want to switch to (0, 1).
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@chukarsten I was thinking we should allow the user to set the threshold as 0 or 1 if they wanted to get the rows closest to those values. What do you think?
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Thank you for making the changes @bchen1116 ! This looks good to me!
Address this issue
Design doc here
Walkthrough use in doc here. The link in this walkthrough should work once we publish the doc to main
API doc here