Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::TablesAnnotation.
Contains annotation details specific to Tables.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#baseline_score
def baseline_score() -> ::Float- (::Float) — Output only. Stores the prediction score for the baseline example, which is defined as the example with all values set to their baseline values. This is used as part of the Sampled Shapley explanation of the model's prediction. This field is populated only when feature importance is requested. For regression models, this holds the baseline prediction for the baseline example. For classification models, this holds the baseline prediction for the baseline example for the argmax class.
#baseline_score=
def baseline_score=(value) -> ::Float- value (::Float) — Output only. Stores the prediction score for the baseline example, which is defined as the example with all values set to their baseline values. This is used as part of the Sampled Shapley explanation of the model's prediction. This field is populated only when feature importance is requested. For regression models, this holds the baseline prediction for the baseline example. For classification models, this holds the baseline prediction for the baseline example for the argmax class.
- (::Float) — Output only. Stores the prediction score for the baseline example, which is defined as the example with all values set to their baseline values. This is used as part of the Sampled Shapley explanation of the model's prediction. This field is populated only when feature importance is requested. For regression models, this holds the baseline prediction for the baseline example. For classification models, this holds the baseline prediction for the baseline example for the argmax class.
#prediction_interval
def prediction_interval() -> ::Google::Cloud::AutoML::V1beta1::DoubleRange-
(::Google::Cloud::AutoML::V1beta1::DoubleRange) — Output only. Only populated when
target_column_spec has FLOAT64 data type. An interval in which the exactly correct target value has 95% chance to be in.
#prediction_interval=
def prediction_interval=(value) -> ::Google::Cloud::AutoML::V1beta1::DoubleRange-
value (::Google::Cloud::AutoML::V1beta1::DoubleRange) — Output only. Only populated when
target_column_spec has FLOAT64 data type. An interval in which the exactly correct target value has 95% chance to be in.
-
(::Google::Cloud::AutoML::V1beta1::DoubleRange) — Output only. Only populated when
target_column_spec has FLOAT64 data type. An interval in which the exactly correct target value has 95% chance to be in.
#score
def score() -> ::Float-
(::Float) — Output only. A confidence estimate between 0.0 and 1.0, inclusive. A higher
value means greater confidence in the returned value.
For
target_column_spec of FLOAT64 data type the score is not populated.
#score=
def score=(value) -> ::Float-
value (::Float) — Output only. A confidence estimate between 0.0 and 1.0, inclusive. A higher
value means greater confidence in the returned value.
For
target_column_spec of FLOAT64 data type the score is not populated.
-
(::Float) — Output only. A confidence estimate between 0.0 and 1.0, inclusive. A higher
value means greater confidence in the returned value.
For
target_column_spec of FLOAT64 data type the score is not populated.
#tables_model_column_info
def tables_model_column_info() -> ::Array<::Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo>-
(::Array<::Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo>) — Output only. Auxiliary information for each of the model's
input_feature_column_specs with respect to this particular prediction. If no other fields than
column_spec_name and
column_display_name would be populated, then this whole field is not.
#tables_model_column_info=
def tables_model_column_info=(value) -> ::Array<::Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo>-
value (::Array<::Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo>) — Output only. Auxiliary information for each of the model's
input_feature_column_specs with respect to this particular prediction. If no other fields than
column_spec_name and
column_display_name would be populated, then this whole field is not.
-
(::Array<::Google::Cloud::AutoML::V1beta1::TablesModelColumnInfo>) — Output only. Auxiliary information for each of the model's
input_feature_column_specs with respect to this particular prediction. If no other fields than
column_spec_name and
column_display_name would be populated, then this whole field is not.
#value
def value() -> ::Google::Protobuf::Value-
(::Google::Protobuf::Value) —
The predicted value of the row's
target_column. The value depends on the column's DataType:
CATEGORY - the predicted (with the above confidence
score) CATEGORY value.FLOAT64 - the predicted (with above
prediction_interval) FLOAT64 value.
#value=
def value=(value) -> ::Google::Protobuf::Value-
value (::Google::Protobuf::Value) —
The predicted value of the row's
target_column. The value depends on the column's DataType:
CATEGORY - the predicted (with the above confidence
score) CATEGORY value.FLOAT64 - the predicted (with above
prediction_interval) FLOAT64 value.
-
(::Google::Protobuf::Value) —
The predicted value of the row's
target_column. The value depends on the column's DataType:
CATEGORY - the predicted (with the above confidence
score) CATEGORY value.FLOAT64 - the predicted (with above
prediction_interval) FLOAT64 value.