Model.deploySQL¶

In [ ]:

Model.deploySQL(key_columns: list = [],
                exclude_columns: list = [],
                X: list = [])

Returns the SQL statement needed to deploy the model.

Parameters¶

Name	Type	Optional	Description
key_columns	list	✓	Predictors used during the algorithm computation which will be deployed with the principal components.
exclude_columns	list	✓	Columns to exclude from the prediction.
X	list	✓	List of the columns used to deploy the model. If empty, the model predictors will be used.

Returns¶

str : the SQL statement needed to deploy the model.

Example¶

In [15]:

from verticapy.learn.preprocessing import Normalizer
model = Normalizer(name = "public.Normalizer_iris")
model.drop()
model.fit("public.iris", ["PetalLengthCm", "SepalLengthCm", "SepalWidthCm"])
display(model.deploySQL())

'APPLY_NORMALIZE("PetalLengthCm", "SepalLengthCm", "SepalWidthCm" USING PARAMETERS model_name = \'public.Normalizer_iris\', match_by_pos = \'true\')'