Class: Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/automl/v1beta1/tables.rb

Overview

An information specific to given column and Tables Model, in context of the Model and the predictions created by it.

Instance Attribute Summary collapse

Instance Attribute Details

#column_display_name ⇒ ::String

Returns Output only. The display name of the column (same as the display_name of its ColumnSpec).

Returns:

  • (::String) —

    Output only. The display name of the column (same as the display_name of its ColumnSpec).



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# File 'proto_docs/google/cloud/automl/v1beta1/tables.rb', line 293

class TablesModelColumnInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end

#column_spec_name ⇒ ::String

Returns Output only. The name of the ColumnSpec describing the column. Not populated when this proto is outputted to BigQuery.

Returns:

  • (::String) —

    Output only. The name of the ColumnSpec describing the column. Not populated when this proto is outputted to BigQuery.



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# File 'proto_docs/google/cloud/automl/v1beta1/tables.rb', line 293

class TablesModelColumnInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end

#feature_importance ⇒ ::Float

Returns 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.

Returns:

  • (::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.



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# File 'proto_docs/google/cloud/automl/v1beta1/tables.rb', line 293

class TablesModelColumnInfo
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end