Feedback

×

• Feedback
• Was this page helpful?*
  • Yes
  • No
• Do you have any additional feedback?
  • Yes
  • No
• Additional Feedback

verticapy.machine_learning.vertica.pipeline.Pipeline.predict

Pipeline.predict(vdf: Annotated[str | vDataFrame, ''] | None = None, X: Annotated[str | list[str], 'STRING representing one column or a list of columns'] | None = None, name: str = 'estimator') → vDataFrame

Applies the model on a vDataFrame.

Parameters

vdf: SQLRelation, optional

Input vDataFrame. You can also specify a customized relation, but you must enclose it with an alias. For example: (SELECT 1) x is valid whereas (SELECT 1) and “SELECT 1” are invalid.

X: SQLColumns, optional

List of the input vDataColumns.

name: str, optional

Name of the added vDataColumn.

Returns

vDataFrame

object result of the model transformation.