The GitHub Actions job "Required Checks" on 
texera.git/fix/7597-gaussiannb-count-vectorizer has failed.
Run started by GitHub user kz930 (triggered by kz930).

Head commit for run:
d44633fda931813dbc2609288aa3817779be0ab2 / kary zheng <[email protected]>
feat(operator): reject Count Vectorizer on the Gaussian Naive Bayes operators

Gaussian Naive Bayes and Training: Gaussian Naive Bayes offered a Count
Vectorizer switch with no working setting. Turning it on ended the execution
from inside scikit-learn: CountVectorizer emits a sparse matrix, and GaussianNB
validates its input without accept_sparse because it estimates a mean and a
variance per feature, which reads the zeros too. The refusal is deliberate on
scikit-learn's side, since densifying a text matrix with a large vocabulary is
what would exhaust memory.

It is specific to this estimator, not to the switch. Fitting
make_pipeline(CountVectorizer(), Estimator()) on the same documents, only
GaussianNB raises; MultinomialNB, BernoulliNB and ComplementNB accept the sparse
matrix, as do the rest of the estimators both groups use. The switch is declared
once on SklearnModelOpDesc and both families splice it in the same way, so all 
of
them inherit it whether or not their estimator can use it.

An estimator that cannot take the sparse matrix now names what to reach for
instead, and the shared getOutputSchemas turns that into a compile-time failure
naming both. Hiding the switch would have been the closer match to how the
family handles an impossible pairing already, but a hide keys on a sibling
field's value and is evaluated in the frontend, so it cannot be made per
estimator on a field the base declares once. It would also leave a workflow
already saved with the switch on still failing at run time.

The message names the estimator and the three Naive Bayes variants that do
accept the matrix. Nothing fires while the switch is off, which is its default,
so a freshly dropped operator is not reported invalid before it is configured.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>

Report URL: https://github.com/apache/texera/actions/runs/31644285834

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