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VertexAIModel(
endpoint: str,
input: typing.Mapping[str, str],
output: typing.Mapping[str, str],
*,
session: typing.Optional[bigframes.session.Session] = None,
connection_name: typing.Optional[str] = None
)
Remote model from a Vertex AI HTTPS endpoint. User must specify HTTPS endpoint, input schema and output schema. For more information, see Deploy model on Vertex AI: https://cloud.google.com/bigquery/docs/bigquery-ml-remote-model-tutorial#Deploy-Model-on-Vertex-AI.
Parameters |
|
---|---|
Name | Description |
endpoint |
str
Vertex AI HTTPS endpoint. |
input |
Mapping
Input schema:
|
output |
Mapping
Output label schema: |
session |
bigframes.Session or None
BQ session to create the model. If None, use the global default session. |
connection_name |
str or None
Connection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>.
|
Methods
__repr__
__repr__()
Print the estimator's constructor with all non-default parameter values.
get_params
get_params(deep: bool = True) -> typing.Dict[str, typing.Any]
Get parameters for this estimator.
Parameter | |
---|---|
Name | Description |
deep |
bool, default True
Default |
Returns | |
---|---|
Type | Description |
Dictionary |
A dictionary of parameter names mapped to their values. |
predict
predict(
X: typing.Union[
bigframes.dataframe.DataFrame,
bigframes.series.Series,
pandas.core.frame.DataFrame,
pandas.core.series.Series,
]
) -> bigframes.dataframe.DataFrame
Predict the result from the input DataFrame.
Parameter | |
---|---|
Name | Description |
X |
bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series
Input DataFrame or Series, which needs to comply with the input parameter of the model. |
Returns | |
---|---|
Type | Description |
bigframes.dataframe.DataFrame |
DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values. |