verticapy.machine_learning.vertica.ensemble.RandomForestRegressor.export_models#
- static RandomForestRegressor.export_models(name: str, path: str, kind: Literal['pmml', 'vertica', 'vertica_models', 'tensorflow', 'tf', None] | None = None) bool #
Exports machine learning models.
Parameters#
- name: str
Model’s name.
- path: str
Absolute path of an output directory to store the exported models.
Warning
This function operates solely on the server side and is not accessible locally. The
path
provided should match the location where the file(s) will be exported on the server.- kind: str, optional
- One of the following:
pmml
vertica
tensorflow
Returns#
- bool
True
if the model was successfully exported.
Examples#
Let’s consider we’ve fitted a Vertica model named ‘my_model’. It is stored in the ‘my_schema’ schema and available in the Database.
You can export it easily:
from verticapy.machine_learning.vertica.base import VerticaModel VerticaModel.export_models( name = 'my_schema.my_model', kind = 'pmml', # Pick up the export type. )
Warning
This function operates solely on the server side and is not accessible locally.