Interface TablesAnnotationOrBuilder (2.3.6) 

public interface TablesAnnotationOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getBaselineScore()

public abstract float getBaselineScore()

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 baseline_score = 5;

Returns
TypeDescription
float

The baselineScore.

getPredictionInterval()

public abstract DoubleRange getPredictionInterval()

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 prediction_interval = 4;

Returns
TypeDescription
DoubleRange

The predictionInterval.

getPredictionIntervalOrBuilder()

public abstract DoubleRangeOrBuilder getPredictionIntervalOrBuilder()

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 prediction_interval = 4;

Returns
TypeDescription
DoubleRangeOrBuilder

getScore()

public abstract float getScore()

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 score = 1;

Returns
TypeDescription
float

The score.

getTablesModelColumnInfo(int index)

public abstract TablesModelColumnInfo getTablesModelColumnInfo(int index)

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.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

Parameter
NameDescription
indexint
Returns
TypeDescription
TablesModelColumnInfo

getTablesModelColumnInfoCount()

public abstract int getTablesModelColumnInfoCount()

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.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

Returns
TypeDescription
int

getTablesModelColumnInfoList()

public abstract List<TablesModelColumnInfo> getTablesModelColumnInfoList()

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.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

Returns
TypeDescription
List<TablesModelColumnInfo>

getTablesModelColumnInfoOrBuilder(int index)

public abstract TablesModelColumnInfoOrBuilder getTablesModelColumnInfoOrBuilder(int index)

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.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

Parameter
NameDescription
indexint
Returns
TypeDescription
TablesModelColumnInfoOrBuilder

getTablesModelColumnInfoOrBuilderList()

public abstract List<? extends TablesModelColumnInfoOrBuilder> getTablesModelColumnInfoOrBuilderList()

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.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 3;

Returns
TypeDescription
List<? extends com.google.cloud.automl.v1beta1.TablesModelColumnInfoOrBuilder>

getValue()

public abstract Value getValue()

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 value = 2;

Returns
TypeDescription
Value

The value.

getValueOrBuilder()

public abstract ValueOrBuilder getValueOrBuilder()

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 value = 2;

Returns
TypeDescription
ValueOrBuilder

hasPredictionInterval()

public abstract boolean hasPredictionInterval()

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 prediction_interval = 4;

Returns
TypeDescription
boolean

Whether the predictionInterval field is set.

hasValue()

public abstract boolean hasValue()

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 value = 2;

Returns
TypeDescription
boolean

Whether the value field is set.