Class ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry (2.42.0)

public static final class ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry extends GeneratedMessageV3 implements ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Metrics for a single confidence threshold.

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

Inheritance

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

Static Fields

CONFIDENCE_THRESHOLD_FIELD_NUMBER

public static final int CONFIDENCE_THRESHOLD_FIELD_NUMBER
Field Value
Type Description
int

F1_SCORE_AT1_FIELD_NUMBER

public static final int F1_SCORE_AT1_FIELD_NUMBER
Field Value
Type Description
int

F1_SCORE_FIELD_NUMBER

public static final int F1_SCORE_FIELD_NUMBER
Field Value
Type Description
int

FALSE_NEGATIVE_COUNT_FIELD_NUMBER

public static final int FALSE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
Type Description
int

FALSE_POSITIVE_COUNT_FIELD_NUMBER

public static final int FALSE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
Type Description
int

FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER

public static final int FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER
Field Value
Type Description
int

FALSE_POSITIVE_RATE_FIELD_NUMBER

public static final int FALSE_POSITIVE_RATE_FIELD_NUMBER
Field Value
Type Description
int

POSITION_THRESHOLD_FIELD_NUMBER

public static final int POSITION_THRESHOLD_FIELD_NUMBER
Field Value
Type Description
int

PRECISION_AT1_FIELD_NUMBER

public static final int PRECISION_AT1_FIELD_NUMBER
Field Value
Type Description
int

PRECISION_FIELD_NUMBER

public static final int PRECISION_FIELD_NUMBER
Field Value
Type Description
int

RECALL_AT1_FIELD_NUMBER

public static final int RECALL_AT1_FIELD_NUMBER
Field Value
Type Description
int

RECALL_FIELD_NUMBER

public static final int RECALL_FIELD_NUMBER
Field Value
Type Description
int

TRUE_NEGATIVE_COUNT_FIELD_NUMBER

public static final int TRUE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
Type Description
int

TRUE_POSITIVE_COUNT_FIELD_NUMBER

public static final int TRUE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

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

getDescriptor()

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

newBuilder()

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

newBuilder(ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)

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

parseDelimitedFrom(InputStream input)

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

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(byte[] data)

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

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteString data)

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

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(CodedInputStream input)

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

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(InputStream input)

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

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteBuffer data)

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

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

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

parser()

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

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
boolean
Overrides

getConfidenceThreshold()

public float getConfidenceThreshold()

Output only. Metrics are computed with an assumption that the model never returns predictions with score lower than this value.

float confidence_threshold = 1;

Returns
Type Description
float

The confidenceThreshold.

getDefaultInstanceForType()

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

getF1Score()

public float getF1Score()

Output only. The harmonic mean of recall and precision.

float f1_score = 4;

Returns
Type Description
float

The f1Score.

getF1ScoreAt1()

public float getF1ScoreAt1()

Output only. The harmonic mean of recall_at1 and precision_at1.

float f1_score_at1 = 7;

Returns
Type Description
float

The f1ScoreAt1.

getFalseNegativeCount()

public long getFalseNegativeCount()

Output only. The number of ground truth labels that are not matched by a model created label.

int64 false_negative_count = 12;

Returns
Type Description
long

The falseNegativeCount.

getFalsePositiveCount()

public long getFalsePositiveCount()

Output only. The number of model created labels that do not match a ground truth label.

int64 false_positive_count = 11;

Returns
Type Description
long

The falsePositiveCount.

getFalsePositiveRate()

public float getFalsePositiveRate()

Output only. False Positive Rate for the given confidence threshold.

float false_positive_rate = 8;

Returns
Type Description
float

The falsePositiveRate.

getFalsePositiveRateAt1()

public float getFalsePositiveRateAt1()

Output only. The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

float false_positive_rate_at1 = 9;

Returns
Type Description
float

The falsePositiveRateAt1.

getParserForType()

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

getPositionThreshold()

public int getPositionThreshold()

Output only. Metrics are computed with an assumption that the model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the confidence_threshold.

int32 position_threshold = 14;

Returns
Type Description
int

The positionThreshold.

getPrecision()

public float getPrecision()

Output only. Precision for the given confidence threshold.

float precision = 3;

Returns
Type Description
float

The precision.

getPrecisionAt1()

public float getPrecisionAt1()

Output only. The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

float precision_at1 = 6;

Returns
Type Description
float

The precisionAt1.

getRecall()

public float getRecall()

Output only. Recall (True Positive Rate) for the given confidence threshold.

float recall = 2;

Returns
Type Description
float

The recall.

getRecallAt1()

public float getRecallAt1()

Output only. The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

float recall_at1 = 5;

Returns
Type Description
float

The recallAt1.

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
int
Overrides

getTrueNegativeCount()

public long getTrueNegativeCount()

Output only. The number of labels that were not created by the model, but if they would, they would not match a ground truth label.

int64 true_negative_count = 13;

Returns
Type Description
long

The trueNegativeCount.

getTruePositiveCount()

public long getTruePositiveCount()

Output only. The number of model created labels that match a ground truth label.

int64 true_positive_count = 10;

Returns
Type Description
long

The truePositiveCount.

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

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

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

writeTo(CodedOutputStream output)

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