The GitHub Actions job "Backport Auto Label" on texera.git/fix-sklearn-empty-cell has succeeded. Run started by GitHub user kz930 (triggered by kz930).
Head commit for run: 17e5144118d0ccb49fe99810d91c2b56eb6498d5 / kary zheng <[email protected]> feat(sklearn): skip rows with missing values instead of ending the run Every Sklearn operator ended the execution when a cell it reads was empty, with an error raised by scikit-learn's own input validation rather than by the operator: ValueError: Input X contains NaN. Nothing in the family looked at missing values, so the message named X, a variable inside generated code, and pointed at neither the column nor the row. An empty value is ordinary input here. A blank CSV cell arrives as null, since univocity returns null for an empty field and AttributeTypeUtils.parseField passes it through by design. Skipping is what the rest of the codebase does with a value that is not there: twenty-four visualization operators open their generated Python with dropna, COUNT counts only non-null rows, CONCAT and MIN pass over them, and FilterPredicate answers false for every condition but IS_NULL / IS_NOT_NULL. This family was the only one with no answer at all. What skipping means follows what each operator emits. The training, classifier and testing operators produce a model, or scores over one, so a dropped row costs nothing the user can see. Training and classifier read every column but the target, so they drop on the whole table; with Count Vectorizer on they read only the text and the target and drop on those two, since a blank in a column they never touch should not cost the row. The advanced trainers read a named list of features and drop on that list plus the ground truth. Prediction is the exception. It adds a result column to each input row, so dropping would take the user's row out of the output along with the value the model had nothing to say about. It keeps the row and leaves the result empty, which is what the Hugging Face inference operators already do with a row they cannot process. Fitting on fewer rows changes the model, the way COUNT over a column with nulls changes the count. That trade is one this codebase has already made everywhere else, and it beats ending the run. Closes #7582 Generated-by: Claude Code (Claude Opus 5) Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Report URL: https://github.com/apache/texera/actions/runs/31546679878 With regards, GitHub Actions via GitBox
