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Model(
model_ref: typing.Optional[
typing.Union[google.cloud.bigquery.model.ModelReference, str]
]
)Model represents a machine learning model resource.
See https://cloud.google.com/bigquery/docs/reference/rest/v2/models
Properties
best_trial_id
The best trial_id across all training runs.
Read-only.
created
Datetime at which the model was created (:data:None until set from the server).
Read-only.
dataset_id
ID of dataset containing the model.
description
Description of the model (defaults to :data:None).
encryption_configuration
Custom encryption configuration for the model.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:None
if using default encryption.
See protecting data with Cloud KMS keys
<https://cloud.google.com/bigquery/docs/customer-managed-encryption>;_
in the BigQuery documentation.
etag
ETag for the model resource (:data:None until set from the server).
Read-only.
expires
The datetime when this model expires.
If not present, the model will persist indefinitely. Expired models will be deleted and their storage reclaimed.
feature_columns
Input feature columns that were used to train this model.
Read-only.
friendly_name
Title of the table (defaults to :data:None).
label_columns
Label columns that were used to train this model.
The output of the model will have a predicted_ prefix to these columns.
Read-only.
labels
Labels for the table.
This method always returns a dict. To change a model's labels, modify the dict,
then call Client.update_model. To delete a label, set its value to
:data:None before updating.
location
The geographic location where the model resides.
This value is inherited from the dataset.
Read-only.
model_id
The model ID.
model_type
Type of the model resource.
Read-only.
modified
Datetime at which the model was last modified (:data:None until set from the server).
Read-only.
path
URL path for the model's APIs.
project
Project bound to the model.
reference
A model reference pointing to this model.
Read-only.
training_runs
Information for all training runs in increasing order of start time.
Dictionaries are in REST API format. See: https://cloud.google.com/bigquery/docs/reference/rest/v2/models#trainingrun
Read-only.
transform_columns
The input feature columns that were used to train this model. The output transform columns used to train this model.
See REST API: https://cloud.google.com/bigquery/docs/reference/rest/v2/models#transformcolumn
Read-only.
Methods
from_api_repr
from_api_repr(
resource: typing.Dict[str, typing.Any]
) -> google.cloud.bigquery.model.ModelFactory: construct a model resource given its API representation
to_api_repr
to_api_repr() -> typing.Dict[str, typing.Any]Construct the API resource representation of this model.
__init__
__init__(
model_ref: typing.Optional[
typing.Union[google.cloud.bigquery.model.ModelReference, str]
]
)Initialize self. See help(type(self)) for accurate signature.
Model
Model(
model_ref: typing.Optional[
typing.Union[google.cloud.bigquery.model.ModelReference, str]
]
)Model represents a machine learning model resource.
See https://cloud.google.com/bigquery/docs/reference/rest/v2/models