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XGBoostModel
(
model_path
:
str
,
*
,
input
:
typing
.
Mapping
[
str
,
str
]
=
{},
output
:
typing
.
Mapping
[
str
,
str
]
=
{},
session
:
typing
.
Optional
[
bigframes
.
session
.
Session
]
=
None
)
Imported XGBoost model.
Parameters
model_path
str
Cloud Storage path that holds the model files.
input
Dict, default None
Specify the model input schema information when you create the XGBoost model. The input should be the format of {field_name: field_type}. Input is optional only if feature_names and feature_types are both specified in the model file. Supported types are "bool", "string", "int64", "float64", "array
output
Dict, default None
Specify the model output schema information when you create the XGBoost model. The input should be the format of {field_name: field_type}. Output is optional only if feature_names and feature_types are both specified in the model file. Supported types are "bool", "string", "int64", "float64", "array
session
BigQuery Session
BQ session to create the model.
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.
deep
bool, default True
Default True
. If True, will return the parameters for this estimator and contained subobjects that are estimators.
Dictionary
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 input DataFrame.
X
bigframes.dataframe.DataFrame
or bigframes.series.Series
or pandas.core.frame.DataFrame or pandas.core.series.Series
Input DataFrame or Series. Schema is defined by the model.
register
register
(
vertex_ai_model_id
:
typing
.
Optional
[
str
]
=
None
)
-
> bigframes
.
ml
.
base
.
_T
Register the model to Vertex AI.
After register, go to the Google Cloud console ( https://console.cloud.google.com/vertex-ai/models ) to manage the model registries. Refer to https://cloud.google.com/vertex-ai/docs/model-registry/introduction for more options.
vertex_ai_model_id
Optional[str], default None
Optional string id as model id in Vertex. If not set, will default to 'bigframes_{bq_model_id}'. Vertex Ai model id will be truncated to 63 characters due to its limitation.
to_gbq
to_gbq
(
model_name
:
str
,
replace
:
bool
=
False
)
-
> bigframes
.
ml
.
imported
.
XGBoostModel
Save the model to BigQuery.
model_name
str
The name of the model.
replace
bool, default False
Determine whether to replace if the model already exists. Default to False.
XGBoostModel
