Class ClassificationEvaluationMetrics (2.35.0)

public final class ClassificationEvaluationMetrics extends GeneratedMessageV3 implements ClassificationEvaluationMetricsOrBuilder

Model evaluation metrics for classification problems. Note: For Video Classification this metrics only describe quality of the Video Classification predictions of "segment_classification" type.

Protobuf type google.cloud.automl.v1.ClassificationEvaluationMetrics

Inheritance

Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > ClassificationEvaluationMetrics

Static Fields

ANNOTATION_SPEC_ID_FIELD_NUMBER

public static final int ANNOTATION_SPEC_ID_FIELD_NUMBER
Field Value
TypeDescription
int

AU_PRC_FIELD_NUMBER

public static final int AU_PRC_FIELD_NUMBER
Field Value
TypeDescription
int

AU_ROC_FIELD_NUMBER

public static final int AU_ROC_FIELD_NUMBER
Field Value
TypeDescription
int

CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER

public static final int CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER
Field Value
TypeDescription
int

CONFUSION_MATRIX_FIELD_NUMBER

public static final int CONFUSION_MATRIX_FIELD_NUMBER
Field Value
TypeDescription
int

LOG_LOSS_FIELD_NUMBER

public static final int LOG_LOSS_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static ClassificationEvaluationMetrics getDefaultInstance()
Returns
TypeDescription
ClassificationEvaluationMetrics

getDescriptor()

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

newBuilder()

public static ClassificationEvaluationMetrics.Builder newBuilder()
Returns
TypeDescription
ClassificationEvaluationMetrics.Builder

newBuilder(ClassificationEvaluationMetrics prototype)

public static ClassificationEvaluationMetrics.Builder newBuilder(ClassificationEvaluationMetrics prototype)
Parameter
NameDescription
prototypeClassificationEvaluationMetrics
Returns
TypeDescription
ClassificationEvaluationMetrics.Builder

parseDelimitedFrom(InputStream input)

public static ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseFrom(byte[] data)

public static ClassificationEvaluationMetrics parseFrom(byte[] data)
Parameter
NameDescription
databyte[]
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
databyte[]
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ClassificationEvaluationMetrics parseFrom(ByteString data)
Parameter
NameDescription
dataByteString
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteString
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ClassificationEvaluationMetrics parseFrom(CodedInputStream input)
Parameter
NameDescription
inputCodedInputStream
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseFrom(InputStream input)

public static ClassificationEvaluationMetrics parseFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
IOException

parseFrom(ByteBuffer data)

public static ClassificationEvaluationMetrics parseFrom(ByteBuffer data)
Parameter
NameDescription
dataByteBuffer
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ClassificationEvaluationMetrics parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteBuffer
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ClassificationEvaluationMetrics
Exceptions
TypeDescription
InvalidProtocolBufferException

parser()

public static Parser<ClassificationEvaluationMetrics> parser()
Returns
TypeDescription
Parser<ClassificationEvaluationMetrics>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
NameDescription
objObject
Returns
TypeDescription
boolean
Overrides

getAnnotationSpecId(int index)

public String getAnnotationSpecId(int index)

Output only. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

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. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

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. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

Returns
TypeDescription
int

The count of annotationSpecId.

getAnnotationSpecIdList()

public ProtocolStringList getAnnotationSpecIdList()

Output only. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

Returns
TypeDescription
ProtocolStringList

A list containing the annotationSpecId.

getAuPrc()

public float getAuPrc()

Output only. The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation.

float au_prc = 1;

Returns
TypeDescription
float

The auPrc.

getAuRoc()

public float getAuRoc()

Output only. The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation.

float au_roc = 6;

Returns
TypeDescription
float

The auRoc.

getConfidenceMetricsEntry(int index)

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry getConfidenceMetricsEntry(int index)

Output only. Metrics for each confidence_threshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and position_threshold = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of position_threshold, but from these no aggregated metrics are computed.

repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationEvaluationMetrics.ConfidenceMetricsEntry

getConfidenceMetricsEntryCount()

public int getConfidenceMetricsEntryCount()

Output only. Metrics for each confidence_threshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and position_threshold = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of position_threshold, but from these no aggregated metrics are computed.

repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
TypeDescription
int

getConfidenceMetricsEntryList()

public List<ClassificationEvaluationMetrics.ConfidenceMetricsEntry> getConfidenceMetricsEntryList()

Output only. Metrics for each confidence_threshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and position_threshold = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of position_threshold, but from these no aggregated metrics are computed.

repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
TypeDescription
List<ConfidenceMetricsEntry>

getConfidenceMetricsEntryOrBuilder(int index)

public ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder getConfidenceMetricsEntryOrBuilder(int index)

Output only. Metrics for each confidence_threshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and position_threshold = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of position_threshold, but from these no aggregated metrics are computed.

repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Parameter
NameDescription
indexint
Returns
TypeDescription
ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

getConfidenceMetricsEntryOrBuilderList()

public List<? extends ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder> getConfidenceMetricsEntryOrBuilderList()

Output only. Metrics for each confidence_threshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and position_threshold = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of position_threshold, but from these no aggregated metrics are computed.

repeated .google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
TypeDescription
List<? extends com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder>

getConfusionMatrix()

public ClassificationEvaluationMetrics.ConfusionMatrix getConfusionMatrix()

Output only. Confusion matrix of the evaluation. Only set for MULTICLASS classification problems where number of labels is no more than 10. Only set for model level evaluation, not for evaluation per label.

.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
TypeDescription
ClassificationEvaluationMetrics.ConfusionMatrix

The confusionMatrix.

getConfusionMatrixOrBuilder()

public ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder getConfusionMatrixOrBuilder()

Output only. Confusion matrix of the evaluation. Only set for MULTICLASS classification problems where number of labels is no more than 10. Only set for model level evaluation, not for evaluation per label.

.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
TypeDescription
ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder

getDefaultInstanceForType()

public ClassificationEvaluationMetrics getDefaultInstanceForType()
Returns
TypeDescription
ClassificationEvaluationMetrics

getLogLoss()

public float getLogLoss()

Output only. The Log Loss metric.

float log_loss = 7;

Returns
TypeDescription
float

The logLoss.

getParserForType()

public Parser<ClassificationEvaluationMetrics> getParserForType()
Returns
TypeDescription
Parser<ClassificationEvaluationMetrics>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
int
Overrides

hasConfusionMatrix()

public boolean hasConfusionMatrix()

Output only. Confusion matrix of the evaluation. Only set for MULTICLASS classification problems where number of labels is no more than 10. Only set for model level evaluation, not for evaluation per label.

.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
TypeDescription
boolean

Whether the confusionMatrix field is set.

hashCode()

public int hashCode()
Returns
TypeDescription
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

newBuilderForType()

public ClassificationEvaluationMetrics.Builder newBuilderForType()
Returns
TypeDescription
ClassificationEvaluationMetrics.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ClassificationEvaluationMetrics.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
NameDescription
parentBuilderParent
Returns
TypeDescription
ClassificationEvaluationMetrics.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
NameDescription
unusedUnusedPrivateParameter
Returns
TypeDescription
Object
Overrides

toBuilder()

public ClassificationEvaluationMetrics.Builder toBuilder()
Returns
TypeDescription
ClassificationEvaluationMetrics.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
NameDescription
outputCodedOutputStream
Overrides
Exceptions
TypeDescription
IOException