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verticapy.machine_learning.vertica.automl.AutoDataPrep.fit

AutoDataPrep.fit(input_relation: Annotated[str | vDataFrame, ''], X: Annotated[str | list[str], 'STRING representing one column or a list of columns'] | None = None, ts: str | None = None, by: Annotated[str | list[str], 'STRING representing one column or a list of columns'] | None = None, return_report: bool = False) → None

Trains the model.

Parameters

input_relation: SQLRelation

Training Relation.

X: SQLColumns, optional

List of the features to preprocess.

ts: str, optional

Time series vDataColumn used to order the data. The vDataColumn type must be date-like (date, datetime, timestamp…).

by: SQLColumns, optional

vDataColumns used in the partition.