Model.deployInverseSQL¶

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

Returns the SQL statement needed to deploy the inverse 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 inverse model.

Example¶

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

REVERSE_NORMALIZE("PetalLengthCm", "SepalLengthCm", "SepalWidthCm" USING PARAMETERS model_name = 'public.norm_iris', match_by_pos = 'true')