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

[Prakhyath07]

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?

[codecov]

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]

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]

Thanks @Prakhyath07 I will fix the CI builds that are failing. There are not related.

[Prakhyath07]

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]

where is 0.10.1?

[glemaitre]

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