Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the What you really need to know section for the big picture.
julearn.prepare.check_consistency#
- julearn.prepare.check_consistency(y, cv, groups, problem_type)#
Check the consistency of the parameters/input.
- Parameters:
- ypandas.Series
The target variable.
- cvint or cross validator object
The cross-validator to use.
- groupspandas.Series | None
The grouping variable.
- problem_typestr
The problem type. Can be “classification” or “regression”.
- Raises:
- ValueError
If there is any inconsistency between the parameters and the data.
- Warns:
- RuntimeWarning
If there might be an inconsistency between the parameters and the data but the pipeline can still run.