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.