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Modify calculate_percent_difference so that it can handle negative values #1100

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merged 4 commits into from
Aug 25, 2020

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freddyaboulton
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Pull Request Description

Let's say for CostBenefitMatrix, the model score is 5 and the baseline score is -10.

Right now, we compute 100 * (5 - (-10))/ -10 = -150%, indicating a decrease in performance when the right answer should be a 150% increase in performance.

This PR fixes that and adds coverage.


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.rst to include this pull request by adding :pr:123.

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codecov bot commented Aug 25, 2020

Codecov Report

Merging #1100 into main will increase coverage by 5.84%.
The diff coverage is 100.00%.

Impacted file tree graph

@@            Coverage Diff             @@
##             main    #1100      +/-   ##
==========================================
+ Coverage   94.06%   99.91%   +5.84%     
==========================================
  Files         192      192              
  Lines       10736    10751      +15     
==========================================
+ Hits        10099    10742     +643     
+ Misses        637        9     -628     
Impacted Files Coverage Δ
evalml/objectives/objective_base.py 100.00% <100.00%> (ø)
...lml/tests/objective_tests/test_standard_metrics.py 100.00% <100.00%> (ø)
evalml/tests/component_tests/test_components.py 100.00% <0.00%> (+0.19%) ⬆️
evalml/automl/automl_search.py 99.56% <0.00%> (+0.43%) ⬆️
...s/prediction_explanations_tests/test_algorithms.py 100.00% <0.00%> (+1.11%) ⬆️
evalml/tests/pipeline_tests/test_pipelines.py 100.00% <0.00%> (+1.38%) ⬆️
evalml/tests/component_tests/test_utils.py 100.00% <0.00%> (+3.57%) ⬆️
...derstanding/prediction_explanations/_algorithms.py 100.00% <0.00%> (+4.28%) ⬆️
evalml/pipelines/pipeline_base.py 100.00% <0.00%> (+5.77%) ⬆️
evalml/tests/utils_tests/test_dependencies.py 100.00% <0.00%> (+6.25%) ⬆️
... and 15 more

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Comment on lines 121 to 128
elif baseline_score < score and cls.greater_is_better:
increase = True
elif baseline_score > score and cls.greater_is_better:
increase = False
elif baseline_score < score and not cls.greater_is_better:
increase = False
else:
increase = True
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Hmm, I wonder if this can be simplified a little? Suggestion:

increase = True
if (baseline_score > score and cls.greater_is_better) or (baseline_score < score and not cls.greater_is_better):
    increase = False

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Good call! Really makes things cleaner. I think I was just being paranoid I would miss a case hehe

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Hahaha I don't blame you, I had to write it all out and make sure too 😂

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@angela97lin angela97lin left a comment

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Test case looks good, just commented on maybe simplifying the checks!

@freddyaboulton freddyaboulton force-pushed the percent-better-baseline-negative-values branch from 0e6d9f0 to 0850cf9 Compare August 25, 2020 16:51
@freddyaboulton freddyaboulton force-pushed the percent-better-baseline-negative-values branch from 0850cf9 to f9dba67 Compare August 25, 2020 17:49
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@dsherry dsherry left a comment

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Lgtm!


increase = True
if (baseline_score > score and cls.greater_is_better) or (baseline_score < score and not cls.greater_is_better):
increase = False
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Cool. My only thought is maybe you can invert it so you don't need the not in not increase

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Done!

@freddyaboulton freddyaboulton merged commit e12671f into main Aug 25, 2020
@dsherry dsherry mentioned this pull request Aug 25, 2020
@freddyaboulton freddyaboulton deleted the percent-better-baseline-negative-values branch October 22, 2020 18:28
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4 participants