Refactor tests for sample weights #11316
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help wanted
Moderate
Anything that requires some knowledge of conventions and best practices
module:test-suite
everything related to our tests
In various parts of the code, we have tests for
sample_weight
support, including in metrics, and for individual estimators. we have some common estimator checks forclass_weight
, but not really forsample_weight
functionality (only for weight type invariance).Recent implementations of
sample_weight
include #10933 (KMeans) and #10803 (density estimation). But as well as estimators we have things like common tests for evaluation metrics.Invariance testing for sample weights should include:
sample_weight=np.ones(len(X))
makes the same model assample_weight=None
sample_weight=random
can make a different model tosample_weight=None
sample_weight=s
for integer arrays
makes the same model asX=np.repeat(X, s, axis=0), y=np.repeat(y, s, axis=0)
(although there may be exceptions to this depending on how the estimator defines iteration, convergence, etc., as in Test test_weighted_vs_repeated is somehow flaky #11236)sample_weight=s * k
for arrays
and positive constantk
makes the same model assample_weight=s
I wonder if it is possible to establish a generic test for this, e.g. something like:
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