verticapy.machine_learning.vertica.decomposition.MCA.import_models#
- static MCA.import_models(path: str, schema: str | None = None, kind: Literal['pmml', 'vertica', 'vertica_models', 'tensorflow', 'tf', None] | None = None) bool #
Imports machine learning models.
Parameters#
- 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.- schema: str, optional
Schema name.
- kind: str, optional
- One of the following:
pmml
vertica
tensorflow
Returns#
- bool
True
if the model was successfully imported.
Examples#
Let’s consider we’ve fitted a Vertica model named ‘my_model’. We want to import it in the ‘my_schema’ schema.
You can import it easily:
from verticapy.machine_learning.vertica.base import VerticaModel VerticaModel.import_models( path = 'server_location' schema = 'my_schema', kind = 'pmml', # Pick up the import type. )
Warning
This function operates solely on the server side and is not accessible locally.