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verticapy.machine_learning.vertica.pipeline.Pipeline.predict#

Pipeline.predict(vdf: str | vDataFrame | None = None, X: str | list[str] | 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.