Class ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry

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
TypeDescription
int

F1_SCORE_AT1_FIELD_NUMBER

public static final int F1_SCORE_AT1_FIELD_NUMBER
Field Value
TypeDescription
int

F1_SCORE_FIELD_NUMBER

public static final int F1_SCORE_FIELD_NUMBER
Field Value
TypeDescription
int

FALSE_NEGATIVE_COUNT_FIELD_NUMBER

public static final int FALSE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

FALSE_POSITIVE_COUNT_FIELD_NUMBER

public static final int FALSE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER

public static final int FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER
Field Value
TypeDescription
int

FALSE_POSITIVE_RATE_FIELD_NUMBER

public static final int FALSE_POSITIVE_RATE_FIELD_NUMBER
Field Value
TypeDescription
int

POSITION_THRESHOLD_FIELD_NUMBER

public static final int POSITION_THRESHOLD_FIELD_NUMBER
Field Value
TypeDescription
int

PRECISION_AT1_FIELD_NUMBER

public static final int PRECISION_AT1_FIELD_NUMBER
Field Value
TypeDescription
int

PRECISION_FIELD_NUMBER

public static final int PRECISION_FIELD_NUMBER
Field Value
TypeDescription
int

RECALL_AT1_FIELD_NUMBER

public static final int RECALL_AT1_FIELD_NUMBER
Field Value
TypeDescription
int

RECALL_FIELD_NUMBER

public static final int RECALL_FIELD_NUMBER
Field Value
TypeDescription
int

TRUE_NEGATIVE_COUNT_FIELD_NUMBER

public static final int TRUE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

TRUE_POSITIVE_COUNT_FIELD_NUMBER

public static final int TRUE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstance()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry

getDescriptor()

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

newBuilder()

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

newBuilder(ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)

public static ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilder(ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
Parameter
NameDescription
prototypeClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder

parseDelimitedFrom(InputStream input)

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

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(byte[] data)

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

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteString data)

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

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(CodedInputStream input)

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

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(InputStream input)

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

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteBuffer data)

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

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

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

parser()

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

Methods

equals(Object obj)

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

The confidenceThreshold.

getDefaultInstanceForType()

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

getF1Score()

public float getF1Score()

Output only. The harmonic mean of recall and precision.

float f1_score = 4;

Returns
TypeDescription
float

The f1Score.

getF1ScoreAt1()

public float getF1ScoreAt1()

Output only. The harmonic mean of recall_at1 and precision_at1.

float f1_score_at1 = 7;

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
long

The falsePositiveCount.

getFalsePositiveRate()

public float getFalsePositiveRate()

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

float false_positive_rate = 8;

Returns
TypeDescription
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
TypeDescription
float

The falsePositiveRateAt1.

getParserForType()

public Parser<ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry> getParserForType()
Returns
TypeDescription
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
TypeDescription
int

The positionThreshold.

getPrecision()

public float getPrecision()

Output only. Precision for the given confidence threshold.

float precision = 3;

Returns
TypeDescription
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
TypeDescription
float

The precisionAt1.

getRecall()

public float getRecall()

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

float recall = 2;

Returns
TypeDescription
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
TypeDescription
float

The recallAt1.

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
long

The truePositiveCount.

getUnknownFields()

public final UnknownFieldSet getUnknownFields()
Returns
TypeDescription
UnknownFieldSet
Overrides

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 ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilderForType()
Returns
TypeDescription
ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

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

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

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

toBuilder()

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

writeTo(CodedOutputStream output)

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