Class TablesAnnotation.Builder (2.2.3)

public static final class TablesAnnotation.Builder extends GeneratedMessageV3.Builder<TablesAnnotation.Builder> implements TablesAnnotationOrBuilder

Contains annotation details specific to Tables.

Protobuf type google.cloud.automl.v1beta1.TablesAnnotation

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addAllTablesModelColumnInfo(Iterable<? extends TablesModelColumnInfo> values)

public TablesAnnotation.Builder addAllTablesModelColumnInfo(Iterable<? extends TablesModelColumnInfo> values)

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
valuesIterable<? extends com.google.cloud.automl.v1beta1.TablesModelColumnInfo>
Returns
TypeDescription
TablesAnnotation.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TablesAnnotation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

addTablesModelColumnInfo(TablesModelColumnInfo value)

public TablesAnnotation.Builder addTablesModelColumnInfo(TablesModelColumnInfo value)

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
valueTablesModelColumnInfo
Returns
TypeDescription
TablesAnnotation.Builder

addTablesModelColumnInfo(TablesModelColumnInfo.Builder builderForValue)

public TablesAnnotation.Builder addTablesModelColumnInfo(TablesModelColumnInfo.Builder builderForValue)

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
builderForValueTablesModelColumnInfo.Builder
Returns
TypeDescription
TablesAnnotation.Builder

addTablesModelColumnInfo(int index, TablesModelColumnInfo value)

public TablesAnnotation.Builder addTablesModelColumnInfo(int index, TablesModelColumnInfo value)

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;

Parameters
NameDescription
indexint
valueTablesModelColumnInfo
Returns
TypeDescription
TablesAnnotation.Builder

addTablesModelColumnInfo(int index, TablesModelColumnInfo.Builder builderForValue)

public TablesAnnotation.Builder addTablesModelColumnInfo(int index, TablesModelColumnInfo.Builder builderForValue)

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;

Parameters
NameDescription
indexint
builderForValueTablesModelColumnInfo.Builder
Returns
TypeDescription
TablesAnnotation.Builder

addTablesModelColumnInfoBuilder()

public TablesModelColumnInfo.Builder addTablesModelColumnInfoBuilder()

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
TablesModelColumnInfo.Builder

addTablesModelColumnInfoBuilder(int index)

public TablesModelColumnInfo.Builder addTablesModelColumnInfoBuilder(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.Builder

build()

public TablesAnnotation build()
Returns
TypeDescription
TablesAnnotation

buildPartial()

public TablesAnnotation buildPartial()
Returns
TypeDescription
TablesAnnotation

clear()

public TablesAnnotation.Builder clear()
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

clearBaselineScore()

public TablesAnnotation.Builder clearBaselineScore()

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
TablesAnnotation.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public TablesAnnotation.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public TablesAnnotation.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

clearPredictionInterval()

public TablesAnnotation.Builder clearPredictionInterval()

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
TablesAnnotation.Builder

clearScore()

public TablesAnnotation.Builder clearScore()

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
TablesAnnotation.Builder

This builder for chaining.

clearTablesModelColumnInfo()

public TablesAnnotation.Builder clearTablesModelColumnInfo()

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
TablesAnnotation.Builder

clearValue()

public TablesAnnotation.Builder clearValue()

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
TablesAnnotation.Builder

clone()

public TablesAnnotation.Builder clone()
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

getBaselineScore()

public 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.

getDefaultInstanceForType()

public TablesAnnotation getDefaultInstanceForType()
Returns
TypeDescription
TablesAnnotation

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getPredictionInterval()

public 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.

getPredictionIntervalBuilder()

public DoubleRange.Builder getPredictionIntervalBuilder()

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.Builder

getPredictionIntervalOrBuilder()

public 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 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 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

getTablesModelColumnInfoBuilder(int index)

public TablesModelColumnInfo.Builder getTablesModelColumnInfoBuilder(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.Builder

getTablesModelColumnInfoBuilderList()

public List<TablesModelColumnInfo.Builder> getTablesModelColumnInfoBuilderList()

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<Builder>

getTablesModelColumnInfoCount()

public 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 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 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 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 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.

getValueBuilder()

public Value.Builder getValueBuilder()

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
Builder

getValueOrBuilder()

public 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 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 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.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(TablesAnnotation other)

public TablesAnnotation.Builder mergeFrom(TablesAnnotation other)
Parameter
NameDescription
otherTablesAnnotation
Returns
TypeDescription
TablesAnnotation.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TablesAnnotation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
TablesAnnotation.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public TablesAnnotation.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

mergePredictionInterval(DoubleRange value)

public TablesAnnotation.Builder mergePredictionInterval(DoubleRange value)

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;

Parameter
NameDescription
valueDoubleRange
Returns
TypeDescription
TablesAnnotation.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TablesAnnotation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

mergeValue(Value value)

public TablesAnnotation.Builder mergeValue(Value 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 value = 2;

Parameter
NameDescription
valueValue
Returns
TypeDescription
TablesAnnotation.Builder

removeTablesModelColumnInfo(int index)

public TablesAnnotation.Builder removeTablesModelColumnInfo(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
TablesAnnotation.Builder

setBaselineScore(float value)

public TablesAnnotation.Builder setBaselineScore(float value)

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;

Parameter
NameDescription
valuefloat

The baselineScore to set.

Returns
TypeDescription
TablesAnnotation.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public TablesAnnotation.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

setPredictionInterval(DoubleRange value)

public TablesAnnotation.Builder setPredictionInterval(DoubleRange value)

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;

Parameter
NameDescription
valueDoubleRange
Returns
TypeDescription
TablesAnnotation.Builder

setPredictionInterval(DoubleRange.Builder builderForValue)

public TablesAnnotation.Builder setPredictionInterval(DoubleRange.Builder builderForValue)

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;

Parameter
NameDescription
builderForValueDoubleRange.Builder
Returns
TypeDescription
TablesAnnotation.Builder

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TablesAnnotation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

setScore(float value)

public TablesAnnotation.Builder setScore(float value)

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;

Parameter
NameDescription
valuefloat

The score to set.

Returns
TypeDescription
TablesAnnotation.Builder

This builder for chaining.

setTablesModelColumnInfo(int index, TablesModelColumnInfo value)

public TablesAnnotation.Builder setTablesModelColumnInfo(int index, TablesModelColumnInfo value)

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;

Parameters
NameDescription
indexint
valueTablesModelColumnInfo
Returns
TypeDescription
TablesAnnotation.Builder

setTablesModelColumnInfo(int index, TablesModelColumnInfo.Builder builderForValue)

public TablesAnnotation.Builder setTablesModelColumnInfo(int index, TablesModelColumnInfo.Builder builderForValue)

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;

Parameters
NameDescription
indexint
builderForValueTablesModelColumnInfo.Builder
Returns
TypeDescription
TablesAnnotation.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final TablesAnnotation.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
TablesAnnotation.Builder
Overrides

setValue(Value value)

public TablesAnnotation.Builder setValue(Value 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 value = 2;

Parameter
NameDescription
valueValue
Returns
TypeDescription
TablesAnnotation.Builder

setValue(Value.Builder builderForValue)

public TablesAnnotation.Builder setValue(Value.Builder builderForValue)

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;

Parameter
NameDescription
builderForValueBuilder
Returns
TypeDescription
TablesAnnotation.Builder