LogisticRegression pipeline does not go through

thiamhuat2026 — Sat, 09 May 2026 09:52:47 GMT

[tracking_store.py:77] Experiment names must be less than 257 characters, begin with a letter or number, and may only include dashes (-) or underscores (_). 2026-05-09:09:48:38,114 ERROR [synapse_mlflow_utils.py:390] [fabric mlflow plugin]: <class 'synapse.ml.mlflow.tracking_store.TridentMLflowTrackingStore'>.check_experiment_name_valid exception Experiment names must be less than 257 characters, begin with a letter or number, and may only include dashes (-) or underscores (_). 2026-05-09:09:48:38,134 ERROR [synapse_mlflow_utils.py:390] [fabric mlflow plugin]: <class 'synapse.ml.mlflow.tracking_store.TridentMLflowTrackingStore'>.get_experiment_by_name exception Experiment names must be less than 257 characters, begin with a letter or number, and may only include dashes (-) or underscores (_). 2026-05-09:09:48:38,136 ERROR [default_experiment_registry.py:55] Error find or created notebook/SJD default experiment, please call mlflow.set_experiment to set a valid one before run Traceback (most recent call last): File "/home/trusted-service-user/cluster-env/trident_env/lib/python3.11/site-packages/synapse/ml/mlflow/default_experiment_registry.py", line 52, in get_experiment_id return mlflow.set_experiment(f"{artifact_name}").experiment_id ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Re: LogisticRegression pipeline does not go through

v-anbandari — Mon, 11 May 2026 07:38:26 GMT

Hi thiamhuat2026,
Thank you for reaching out to the Microsoft community Forum.

The issue is not caused by the LogisticRegression pipeline itself. Based on the error message , the failure occurs because the notebook environment automatically tries to create an MLflow experiment during "pipeline.fit(train_df)", but the generated experiment name does not satisfy MLflow experiment naming rules. Because of this, the pipeline execution fails before the model training starts.

To resolve the issue, manually set a valid MLflow experiment name before training the pipeline:

import mlflow mlflow.set_experiment("logistic_regression_experiment")

Then run your existing pipeline code again.

For More Details :
Machine learning experiment - Microsoft Fabric | Microsoft Learn.

I hope this helps. Please feel free to reach out for further queries.
Thank you.

topic LogisticRegression pipeline does not go through in Data Science

LogisticRegression pipeline does not go through

Re: LogisticRegression pipeline does not go through