The ML.GLOBAL_EXPLAIN function
This document describes the ML.GLOBAL_EXPLAIN
function, which lets you provide
explanations for the entire model by aggregating the local explanations of the evaluation data. You can only use ML.GLOBAL_EXPLAIN
with models that are trained with the
ENABLE_GLOBAL_EXPLAIN
option
set to TRUE
.
Syntax
ML.GLOBAL_EXPLAIN( MODEL `project_id.dataset.model_name`, STRUCT( [class_level_explain AS class_level_explain]))
Arguments
ML.GLOBAL_EXPLAIN
takes the following arguments:
-
project_id
: Your project ID. -
dataset
: The BigQuery dataset that contains the model. -
model
: The name of the model. -
class_level_explain
: aBOOL
value that specifies whether global feature importances are returned for each class. Applies only to non-AutoML Tables classification models. When set toFALSE
, the global feature importance of the entire model is returned rather than that of each class. The default value isFALSE
.Regression models and AutoML Tables classification models only have model-level global feature importance.
Output
The output of ML.GLOBAL_EXPLAIN
has two formats:
-
For classification models with
class_level_explain
set toFALSE
, and for regression models, the following columns are returned:-
feature
: aSTRING
value that contains the feature name. -
attribution
: aFLOAT64
value that contains the feature importance to the model overall.
-
-
For classification models with
class_level_explain
set toTRUE
, the following columns are returned:-
<class_name>
: aSTRING
value that contains the name of the class in the label column. -
feature
: aSTRING
value that contains the feature name. -
attribution
: aFLOAT64
value that contains the feature importance to this class.
For each class, only the top 10 most important features are returned.
-
Examples
The following examples assume your model is in your default project.
Regression model
This example gets global feature importance for the boosted tree regression
model mymodel
in mydataset
. The dataset is in your default project.
SELECT * FROM ML.GLOBAL_EXPLAIN(MODEL `mydataset.mymodel`)
Classifier model
This example gets global feature importance for the boosted tree classifier
model mymodel
in mydataset
. The dataset is in your default project.
SELECT * FROM ML.GLOBAL_EXPLAIN(MODEL `mydataset.mymodel`, STRUCT(TRUE AS class_level_explain))
What's next
- For information about Explainable AI, see BigQuery Explainable AI overview.
- For information about the supported SQL statements and functions for each model type, see End-to-end user journey for each model.