verticapy.machine_learning.vertica.TensorFlowModel.predict#

TensorFlowModel.predict(vdf: str | vDataFrame, X: str | list[str] | None = None, name: str | None = None, inplace: bool = True) → vDataFrame#

Predicts using the input relation.

Parameters#

vdf: SQLRelation: Object used to run the prediction. 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: List of the columns used to deploy the models.
name: str, optional: Name of the added vDataColumn. If empty, a name is generated.

Note

This parameter is only used when the input ‘X’ is a complex data type, otherwise it is ignored.
inplace: bool, optional: If set to True, the prediction is added to the vDataFrame.

Returns#

vDataFrame: the input object.