Class ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder (2.33.0)

public static final class ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder extends GeneratedMessageV3.Builder<ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder> implements ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder

Confusion matrix of the model running the classification.

Protobuf type google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Static Methods

getDescriptor()

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

Methods

addAllAnnotationSpecId(Iterable<String> values)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addAllAnnotationSpecId(Iterable<String> values)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameter
NameDescription
valuesIterable<String>

The annotationSpecId to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addAllDisplayName(Iterable<String> values)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addAllDisplayName(Iterable<String> values)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
NameDescription
valuesIterable<String>

The displayName to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addAllRow(Iterable<? extends ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row> values)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addAllRow(Iterable<? extends ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row> values)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
valuesIterable<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row>
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

addAnnotationSpecId(String value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addAnnotationSpecId(String value)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameter
NameDescription
valueString

The annotationSpecId to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addAnnotationSpecIdBytes(ByteString value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addAnnotationSpecIdBytes(ByteString value)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameter
NameDescription
valueByteString

The bytes of the annotationSpecId to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addDisplayName(String value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addDisplayName(String value)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
NameDescription
valueString

The displayName to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addDisplayNameBytes(ByteString value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addDisplayNameBytes(ByteString value)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
NameDescription
valueByteString

The bytes of the displayName to add.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

addRow(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addRow(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
valueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

addRow(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addRow(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
builderForValueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

addRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameters
NameDescription
indexint
valueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

addRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder addRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameters
NameDescription
indexint
builderForValueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

addRowBuilder()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder addRowBuilder()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

addRowBuilder(int index)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder addRowBuilder(int index)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

build()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix build()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

buildPartial()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix buildPartial()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

clear()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clear()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

clearAnnotationSpecId()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearAnnotationSpecId()

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

clearDisplayName()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearDisplayName()

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

clearRow()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearRow()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

clone()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clone()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

getAnnotationSpecId(int index)

public String getAnnotationSpecId(int index)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameter
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
String

The annotationSpecId at the given index.

getAnnotationSpecIdBytes(int index)

public ByteString getAnnotationSpecIdBytes(int index)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameter
NameDescription
indexint

The index of the value to return.

Returns
TypeDescription
ByteString

The bytes of the annotationSpecId at the given index.

getAnnotationSpecIdCount()

public int getAnnotationSpecIdCount()

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Returns
TypeDescription
int

The count of annotationSpecId.

getAnnotationSpecIdList()

public ProtocolStringList getAnnotationSpecIdList()

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Returns
TypeDescription
ProtocolStringList

A list containing the annotationSpecId.

getDefaultInstanceForType()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix getDefaultInstanceForType()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getDisplayName(int index)

public String getDisplayName(int index)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
NameDescription
indexint

The index of the element to return.

Returns
TypeDescription
String

The displayName at the given index.

getDisplayNameBytes(int index)

public ByteString getDisplayNameBytes(int index)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameter
NameDescription
indexint

The index of the value to return.

Returns
TypeDescription
ByteString

The bytes of the displayName at the given index.

getDisplayNameCount()

public int getDisplayNameCount()

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Returns
TypeDescription
int

The count of displayName.

getDisplayNameList()

public ProtocolStringList getDisplayNameList()

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Returns
TypeDescription
ProtocolStringList

A list containing the displayName.

getRow(int index)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row getRow(int index)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row

getRowBuilder(int index)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder getRowBuilder(int index)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

getRowBuilderList()

public List<ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder> getRowBuilderList()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
List<Builder>

getRowCount()

public int getRowCount()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
int

getRowList()

public List<ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row> getRowList()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
List<Row>

getRowOrBuilder(int index)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.RowOrBuilder getRowOrBuilder(int index)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.RowOrBuilder

getRowOrBuilderList()

public List<? extends ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.RowOrBuilder> getRowOrBuilderList()

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Returns
TypeDescription
List<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.RowOrBuilder>

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix other)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeFrom(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix other)
Parameter
NameDescription
otherClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

mergeFrom(Message other)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides

removeRow(int index)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder removeRow(int index)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

setAnnotationSpecId(int index, String value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setAnnotationSpecId(int index, String value)

Output only. IDs of the annotation specs used in the confusion matrix. For Tables CLASSIFICATION

prediction_type only list of [annotation_spec_display_name-s][] is populated.

repeated string annotation_spec_id = 1;

Parameters
NameDescription
indexint

The index to set the value at.

valueString

The annotationSpecId to set.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

setDisplayName(int index, String value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setDisplayName(int index, String value)

Output only. Display name of the annotation specs used in the confusion matrix, as they were at the moment of the evaluation. For Tables CLASSIFICATION

prediction_type-s, distinct values of the target column at the moment of the model evaluation are populated here.

repeated string display_name = 3;

Parameters
NameDescription
indexint

The index to set the value at.

valueString

The displayName to set.

Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

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

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

setRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row value)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameters
NameDescription
indexint
valueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

setRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setRow(int index, ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder builderForValue)

Output only. Rows in the confusion matrix. The number of rows is equal to the size of annotation_spec_id. row[i].example_count[j] is the number of examples that have ground truth of the annotation_spec_id[i] and are predicted as annotation_spec_id[j] by the model being evaluated.

repeated .google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix.Row row = 2;

Parameters
NameDescription
indexint
builderForValueClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder
Overrides