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FIX make sure to accept "minority" as a valid strategy in over-samplers #964

Merged
merged 3 commits into from
Dec 28, 2022
Merged

FIX make sure to accept "minority" as a valid strategy in over-samplers #964

merged 3 commits into from
Dec 28, 2022

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Prakhyath07
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Reference Issue

What does this implement/fix? Explain your changes.

while using smapling strategy ="minority" we were getting error. i found issue in base.py of oversampler where in _parameter constraint majority was used in stroptions instead of minority

Any other comments?

@Prakhyath07
update oversampler base.py
c4ffc26 
updated majority to minority  in str options:  
_parameter_constraints: dict = {
        "sampling_strategy": [
            Interval(numbers.Real, 0, 1, closed="right"),
            StrOptions({"auto", "minority", "not minority", "not majority", "all"}),
            Mapping,
            callable,
        ],
        "random_state": ["random_state"],
    }
@Prakhyath07
Merge pull request #1 from Prakhyath07/Prakhyath07-patch-1
4bfefba 
update oversampler base.py
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codecov bot commented Dec 23, 2022 •
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Codecov Report

Base: 96.50% // Head: 94.25% // Decreases project coverage by -2.24% ⚠️

Coverage data is based on head (14c4a8b) compared to base (7cead9c).
Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files 
@@            Coverage Diff             @@
##           master     #964      +/-   ##
==========================================
- Coverage   96.50%   94.25%   -2.25%     
==========================================
  Files         103      103              
  Lines        7264     7280      +16     
  Branches     1068     1071       +3     
==========================================
- Hits         7010     6862     -148     
- Misses        147      312     +165     
+ Partials      107      106       -1
Impacted Files Coverage Δ
imblearn/over_sampling/base.py 100.00% <ø> (ø)
...rn/over_sampling/tests/test_random_over_sampler.py 100.00% <100.00%> (ø)
...otype_selection/tests/test_random_under_sampler.py 100.00% <100.00%> (ø)
...ing/_prototype_selection/tests/test_tomek_links.py 100.00% <100.00%> (ø)
imblearn/keras/tests/test_generator.py 9.37% <0.00%> (-90.63%) ⬇️
imblearn/tensorflow/_generator.py 27.58% <0.00%> (-68.97%) ⬇️
imblearn/tensorflow/tests/test_generator.py 10.75% <0.00%> (-54.84%) ⬇️
imblearn/keras/_generator.py 45.20% <0.00%> (-46.58%) ⬇️
imblearn/tests/test_docstring_parameters.py 87.32% <0.00%> (-0.71%) ⬇️

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@glemaitre glemaitre changed the title updated sampling strategy string of oversampler base.py from majority to minority FIX make sure to accept "minority" as a valid strategy in over-samplers Dec 28, 2022
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I added some non-regression tests and an entry in the changelog.
I will probably try to make a release soon because it is a blocker.

@glemaitre glemaitre merged commit 79107e8 into scikit-learn-contrib:master Dec 28, 2022
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Thanks @Prakhyath07 I will fix the CI builds that are failing. There are not related.

glemaitre added a commit that referenced this pull request Dec 28, 2022
@Prakhyath07 @glemaitre
FIX make sure to accept "minority" as a valid strategy in over-sample…
0cc02fd 
…rs (#964)

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
@Prakhyath07
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Reference Issue

What does this implement/fix? Explain your changes.

while using smapling strategy ="minority" we were getting error. i found issue in base.py of oversampler where in _parameter constraint majority was used in stroptions instead of minority

Any other comments?

From my side i didn't find any other issue
Thank you so much

@dront78
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dront78 commented Mar 18, 2023

where is 0.10.1?

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On PyPI and conda-forge, e.g. https://pypi.org/project/imbalanced-learn/

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3 participants
@Prakhyath07 @glemaitre @dront78