[BUG] Mlflow predict method gives wrong results if multi-target modeling is used and pandas dataframe is passed there
Author: pradipneupaneCreated Jul 1, 2024Updated Sep 17, 2026
Labelsbugarea/modelshas-closing-pr
Issues Policy acknowledgement
- I have read and agree to submit bug reports in accordance with the issues policy
Where did you encounter this bug?
Local machine
Willingness to contribute
Yes. I can contribute a fix for this bug independently.
MLflow version
- Client: 2.14.1
System information
..
Describe the problem
I was using onnx model format and when trying with multi-targets using pandas dataframe, it gives wrong results: The issues is this line where it fails to keep those multi-target results in proper orders:
I believe this issues is same for other model flavors also (though I didn't tests those)
If multi-target is passed, then it should handle there accordingly.
Tracking information
exact code is already added in screenshot
Code to reproduce issue
screenshot is already there
Stack trace
stack trace not needed
Other info / logs
example not needed
What component(s) does this bug affect?
-
area/artifacts: Artifact stores and artifact logging -
area/build: Build and test infrastructure for MLflow -
area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations -
area/docs: MLflow documentation pages -
area/examples: Example code -
area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry -
area/models: MLmodel format, model serialization/deserialization, flavors -
area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates -
area/projects: MLproject format, project running backends -
area/scoring: MLflow Model server, model deployment tools, Spark UDFs -
area/server-infra: MLflow Tracking server backend -
area/tracking: Tracking Service, tracking client APIs, autologging
What interface(s) does this bug affect?
-
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server -
area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models -
area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry -
area/windows: Windows support
What language(s) does this bug affect?
-
language/r: R APIs and clients -
language/java: Java APIs and clients -
language/new: Proposals for new client languages
What integration(s) does this bug affect?
-
integrations/azure: Azure and Azure ML integrations -
integrations/sagemaker: SageMaker integrations -
integrations/databricks: Databricks integrations
Source: mlflow/mlflow