Class ClassificationProto.ClassificationEvaluationMetrics (2.44.0)

public static final class ClassificationProto.ClassificationEvaluationMetrics extends GeneratedMessageV3 implements ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics

Inheritance

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

Static Fields

ANNOTATION_SPEC_ID_FIELD_NUMBER

public static final int ANNOTATION_SPEC_ID_FIELD_NUMBER
Field Value
Type Description
int

AU_PRC_FIELD_NUMBER

public static final int AU_PRC_FIELD_NUMBER
Field Value
Type Description
int

AU_ROC_FIELD_NUMBER

public static final int AU_ROC_FIELD_NUMBER
Field Value
Type Description
int

BASE_AU_PRC_FIELD_NUMBER

public static final int BASE_AU_PRC_FIELD_NUMBER
Field Value
Type Description
int

CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER

public static final int CONFIDENCE_METRICS_ENTRY_FIELD_NUMBER
Field Value
Type Description
int

CONFUSION_MATRIX_FIELD_NUMBER

public static final int CONFUSION_MATRIX_FIELD_NUMBER
Field Value
Type Description
int

LOG_LOSS_FIELD_NUMBER

public static final int LOG_LOSS_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

public static ClassificationProto.ClassificationEvaluationMetrics getDefaultInstance()
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

newBuilder()

public static ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilder()
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.Builder

newBuilder(ClassificationProto.ClassificationEvaluationMetrics prototype)

public static ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilder(ClassificationProto.ClassificationEvaluationMetrics prototype)
Parameter
Name Description
prototype ClassificationProto.ClassificationEvaluationMetrics
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.Builder

parseDelimitedFrom(InputStream input)

public static ClassificationProto.ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseFrom(byte[] data)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(byte[] data)
Parameter
Name Description
data byte[]
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data byte[]
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteString data)
Parameter
Name Description
data ByteString
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteString
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(CodedInputStream input)
Parameter
Name Description
input CodedInputStream
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseFrom(InputStream input)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
IOException

parseFrom(ByteBuffer data)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteBuffer data)
Parameter
Name Description
data ByteBuffer
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ClassificationProto.ClassificationEvaluationMetrics parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteBuffer
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics
Exceptions
Type Description
InvalidProtocolBufferException

parser()

public static Parser<ClassificationProto.ClassificationEvaluationMetrics> parser()
Returns
Type Description
Parser<ClassificationEvaluationMetrics>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
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
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. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

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. The annotation spec ids used for this evaluation.

repeated string annotation_spec_id = 5;

Returns
Type Description
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
Type Description
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
Type Description
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
Type Description
float

The auRoc.

getBaseAuPrc() (deprecated)

public float getBaseAuPrc()

Deprecated. google.cloud.automl.v1beta1.ClassificationEvaluationMetrics.base_au_prc is deprecated. See google/cloud/automl/v1beta1/classification.proto;l=188

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

float base_au_prc = 2 [deprecated = true];

Returns
Type Description
float

The baseAuPrc.

getConfidenceMetricsEntry(int index)

public ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Parameter
Name Description
index int
Returns
Type Description
ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
Type Description
int

getConfidenceMetricsEntryList()

public List<ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
Type Description
List<ConfidenceMetricsEntry>

getConfidenceMetricsEntryOrBuilder(int index)

public ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Parameter
Name Description
index int
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

getConfidenceMetricsEntryOrBuilderList()

public List<? extends ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry confidence_metrics_entry = 3;

Returns
Type Description
List<? extends com.google.cloud.automl.v1beta1.ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder>

getConfusionMatrix()

public ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrix

The confusionMatrix.

getConfusionMatrixOrBuilder()

public ClassificationProto.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.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.ConfusionMatrixOrBuilder

getDefaultInstanceForType()

public ClassificationProto.ClassificationEvaluationMetrics getDefaultInstanceForType()
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics

getLogLoss()

public float getLogLoss()

Output only. The Log Loss metric.

float log_loss = 7;

Returns
Type Description
float

The logLoss.

getParserForType()

public Parser<ClassificationProto.ClassificationEvaluationMetrics> getParserForType()
Returns
Type Description
Parser<ClassificationEvaluationMetrics>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
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.v1beta1.ClassificationEvaluationMetrics.ConfusionMatrix confusion_matrix = 4;

Returns
Type Description
boolean

Whether the confusionMatrix field is set.

hashCode()

public int hashCode()
Returns
Type Description
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

newBuilderForType()

public ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilderForType()
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ClassificationProto.ClassificationEvaluationMetrics.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Name Description
parent BuilderParent
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Name Description
unused UnusedPrivateParameter
Returns
Type Description
Object
Overrides

toBuilder()

public ClassificationProto.ClassificationEvaluationMetrics.Builder toBuilder()
Returns
Type Description
ClassificationProto.ClassificationEvaluationMetrics.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
Name Description
output CodedOutputStream
Overrides
Exceptions
Type Description
IOException