An information specific to given column and Tables Model, in
context of the Model and the predictions created by it.
Attributes
Name
Description
column_spec_name
str
Output only. The name of the ColumnSpec
describing the column. Not populated when this
proto is outputted to BigQuery.
column_display_name
str
Output only. The display name of the column (same as the
display_name of its ColumnSpec).
feature_importance
float
Output only. When given as part of a Model (always
populated): Measurement of how much model predictions
correctness on the TEST data depend on values in this
column. A value between 0 and 1, higher means higher
influence. These values are normalized - for all input
feature columns of a given model they add to 1.
When given back by Predict (populated iff
[feature_importance
param][google.cloud.automl.v1beta1.PredictRequest.params] is
set) or Batch Predict (populated iff
feature_importance
param is set): Measurement of how impactful for the
prediction returned for the given row the value in this
column was. Specifically, the feature importance specifies
the marginal contribution that the feature made to the
prediction score compared to the baseline score. These
values are computed using the Sampled Shapley method.