Class ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder (2.1.23)

Version 2.1.23

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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

Implements

ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
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

Name	Description
values	Iterable<String> The annotationSpecId to add.

Returns

Type	Description
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

Name	Description
values	Iterable<String> The displayName to add.

Returns

Type	Description
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

Name	Description
values	Iterable<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row>

Returns

Type	Description
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

Name	Description
value	String The annotationSpecId to add.

Returns

Type	Description
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

Name	Description
value	ByteString The bytes of the annotationSpecId to add.

Returns

Type	Description
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

Name	Description
value	String The displayName to add.

Returns

Type	Description
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

Name	Description
value	ByteString The bytes of the displayName to add.

Returns

Type	Description
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

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

Name	Description
value	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row

Returns

Type	Description
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

Name	Description
builderForValue	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

Returns

Type	Description
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

Name	Description
index	int
value	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row

Returns

Type	Description
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

Name	Description
index	int
builderForValue	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

Returns

Type	Description
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

Type	Description
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

Name	Description
index	int

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

build()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix build()

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

buildPartial()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix buildPartial()

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

clear()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clear()

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

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

Type	Description
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

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearOneof(Descriptors.OneofDescriptor oneof)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

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

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

clone()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder clone()

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

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

Name	Description
index	int The index of the element to return.

Returns

Type	Description
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

Name	Description
index	int The index of the value to return.

Returns

Type	Description
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

Type	Description
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

Type	Description
ProtocolStringList	A list containing the annotationSpecId.

getDefaultInstanceForType()

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix getDefaultInstanceForType()

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

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

Name	Description
index	int The index of the element to return.

Returns

Type	Description
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

Name	Description
index	int The index of the value to return.

Returns

Type	Description
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

Type	Description
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

Type	Description
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

Name	Description
index	int

Returns

Type	Description
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

Name	Description
index	int

Returns

Type	Description
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

Type	Description
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

Type	Description
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

Type	Description
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

Name	Description
index	int

Returns

Type	Description
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

Type	Description
List<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.RowOrBuilder>

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix other)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeFrom(ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix other)

Parameter

Name	Description
other	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

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

Name	Description
index	int

Returns

Type	Description
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

Name	Description
index	int The index to set the value at.
value	String The annotationSpecId to set.

Returns

Type	Description
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

Name	Description
index	int The index to set the value at.
value	String The displayName to set.

Returns

Type	Description
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

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

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

public ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

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

Name	Description
index	int
value	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row

Returns

Type	Description
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

Name	Description
index	int
builderForValue	ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Row.Builder

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)