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Posted to notifications@texera.apache.org by "kz930 (via GitHub)" <gi...@apache.org> on 2026/08/25 00:01:55 UTC
[I] The SVM Regressor trainer offers a hyperparameter named `probability`, which sets `shrinking` instead [texera]
kz930 opened a new issue, #7949:
URL: https://github.com/apache/texera/issues/7949
### What happened?
The Advanced SVM Regressor Trainer offers a hyperparameter called `probability` in its Parameter dropdown. Choosing it sets `shrinking`.
The dropdown shows the name of the enum constant, while the emitted Python passes the keyword that constant carries. `SklearnAdvancedSVRParameters` declares the constant as `probability("shrinking", ...)`, so the two differ for this one parameter and agree for every other one the operator offers.
`shrinking` is the correct keyword. Read off the estimator's own signature, `SVR` takes `kernel`, `degree`, `gamma`, `coef0`, `tol`, `C`, `epsilon`, `shrinking`, `cache_size`, `verbose` and `max_iter`, and has no `probability` at all. `SVC` has both, which is where the name looks to have come from: the enum reads like a copy of the SVC one where the keyword was updated and the constant name was not.
So nothing is missing from the operator, and the emitted code is right. What is wrong is the name the user picks it by. Someone who wants to turn shrinking off has to know to look for a parameter named after a different one, and someone who picks `probability` expecting probability estimates changes shrinking instead and is told nothing.
The fix is to rename the constant to `shrinking`. A workflow saved before that carries `"probability"` in its config and would no longer deserialize, so whether to keep the old name readable is worth deciding in the PR rather than here.
### How to reproduce?
Add an Advanced SVM Regressor Trainer, wire a numeric table to its training port and any table to its parameter port, then set the ground truth attribute and the selected features. Add one hyperparameter row and open the Parameter dropdown: `probability` is offered. Pick it, give it `true`, and run. The generated code passes `shrinking = ...`, and the estimator's `probability` is never touched, there being no such parameter to touch.
### Version/Branch
1.3.0-incubating-SNAPSHOT (main)
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Re: [I] The SVM Regressor trainer offers a hyperparameter named `probability`, which sets `shrinking` instead [texera]
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on issue #7949:
URL: https://github.com/apache/texera/issues/7949#issuecomment-5403113847
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Re: [I] The SVM Regressor trainer offers a hyperparameter named `probability`, which sets `shrinking` instead [texera]
Posted by "VuMartin (via GitHub)" <gi...@apache.org>.
VuMartin commented on issue #7949:
URL: https://github.com/apache/texera/issues/7949#issuecomment-5407379091
/take
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Re: [I] The SVM Regressor trainer offers a hyperparameter named `probability`, which sets `shrinking` instead [texera]
Posted by "aglinxinyuan (via GitHub)" <gi...@apache.org>.
aglinxinyuan closed issue #7949: The SVM Regressor trainer offers a hyperparameter named `probability`, which sets `shrinking` instead
URL: https://github.com/apache/texera/issues/7949
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