Package com.google.cloud.automl.v1

Class ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

com.google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder

All Implemented Interfaces:

ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable

Enclosing class:

ClassificationEvaluationMetrics.ConfidenceMetricsEntry

public static final class ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder
extends com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>
implements ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

 Metrics for a single confidence threshold.
 

Protobuf type google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry

Method Summary

Modifier and Type	Method	Description
ClassificationEvaluationMetrics.ConfidenceMetricsEntry	build()
ClassificationEvaluationMetrics.ConfidenceMetricsEntry	buildPartial()
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clear()
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearConfidenceThreshold()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearF1Score()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearF1ScoreAt1()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearFalseNegativeCount()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearFalsePositiveCount()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearFalsePositiveRate()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearFalsePositiveRateAt1()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearPositionThreshold()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearPrecision()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearPrecisionAt1()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearRecall()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearRecallAt1()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearTrueNegativeCount()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	clearTruePositiveCount()	Output only.
float	getConfidenceThreshold()	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry	getDefaultInstanceForType()
static final com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
float	getF1Score()	Output only.
float	getF1ScoreAt1()	Output only.
long	getFalseNegativeCount()	Output only.
long	getFalsePositiveCount()	Output only.
float	getFalsePositiveRate()	Output only.
float	getFalsePositiveRateAt1()	Output only.
int	getPositionThreshold()	Output only.
float	getPrecision()	Output only.
float	getPrecisionAt1()	Output only.
float	getRecall()	Output only.
float	getRecallAt1()	Output only.
long	getTrueNegativeCount()	Output only.
long	getTruePositiveCount()	Output only.
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable	internalGetFieldAccessorTable()
final boolean	isInitialized()
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	mergeFrom(ClassificationEvaluationMetrics.ConfidenceMetricsEntry other)
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	mergeFrom(com.google.protobuf.Message other)
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setConfidenceThreshold(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setF1Score(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setF1ScoreAt1(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setFalseNegativeCount(long value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setFalsePositiveCount(long value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setFalsePositiveRate(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setFalsePositiveRateAt1(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setPositionThreshold(int value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setPrecision(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setPrecisionAt1(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setRecall(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setRecallAt1(float value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setTrueNegativeCount(long value)	Output only.
ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder	setTruePositiveCount(long value)	Output only.

Methods inherited from class com.google.protobuf.GeneratedMessage.Builder

addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

Methods inherited from interface com.google.protobuf.MessageLite.Builder

mergeFrom

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Method Details

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable

protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()

Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

clear

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clear()

Specified by:

clear in interface com.google.protobuf.Message.Builder

Specified by:

clear in interface com.google.protobuf.MessageLite.Builder

Overrides:

clear in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

getDescriptorForType

public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface com.google.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

getDefaultInstanceForType

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstanceForType()

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

build

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry build()

Specified by:

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

buildPartial

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry buildPartial()

Specified by:

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

mergeFrom

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(com.google.protobuf.Message other)

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

mergeFrom

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(ClassificationEvaluationMetrics.ConfidenceMetricsEntry other)

isInitialized

public final boolean isInitialized()

Specified by:

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

mergeFrom

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(com.google.protobuf.CodedInputStream input,
 com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                                                         throws IOException

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Specified by:

mergeFrom in interface com.google.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>

Throws:

IOException

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;

Specified by:

getConfidenceThreshold in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The confidenceThreshold.

setConfidenceThreshold

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setConfidenceThreshold(float value)

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

float confidence_threshold = 1;

Parameters:

value - The confidenceThreshold to set.

Returns:

This builder for chaining.

clearConfidenceThreshold

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearConfidenceThreshold()

 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:

This builder for chaining.

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;

Specified by:

getPositionThreshold in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The positionThreshold.

setPositionThreshold

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setPositionThreshold(int value)

 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;

Parameters:

value - The positionThreshold to set.

Returns:

This builder for chaining.

clearPositionThreshold

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearPositionThreshold()

 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:

This builder for chaining.

getRecall

public float getRecall()

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

float recall = 2;

Specified by:

getRecall in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The recall.

setRecall

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setRecall(float value)

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

float recall = 2;

Parameters:

value - The recall to set.

Returns:

This builder for chaining.

clearRecall

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearRecall()

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

float recall = 2;

Returns:

This builder for chaining.

getPrecision

public float getPrecision()

 Output only. Precision for the given confidence threshold.
 

float precision = 3;

Specified by:

getPrecision in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The precision.

setPrecision

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setPrecision(float value)

 Output only. Precision for the given confidence threshold.
 

float precision = 3;

Parameters:

value - The precision to set.

Returns:

This builder for chaining.

clearPrecision

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearPrecision()

 Output only. Precision for the given confidence threshold.
 

float precision = 3;

Returns:

This builder for chaining.

getFalsePositiveRate

public float getFalsePositiveRate()

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

float false_positive_rate = 8;

Specified by:

getFalsePositiveRate in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The falsePositiveRate.

setFalsePositiveRate

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setFalsePositiveRate(float value)

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

float false_positive_rate = 8;

Parameters:

value - The falsePositiveRate to set.

Returns:

This builder for chaining.

clearFalsePositiveRate

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearFalsePositiveRate()

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

float false_positive_rate = 8;

Returns:

This builder for chaining.

getF1Score

public float getF1Score()

 Output only. The harmonic mean of recall and precision.
 

float f1_score = 4;

Specified by:

getF1Score in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The f1Score.

setF1Score

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setF1Score(float value)

 Output only. The harmonic mean of recall and precision.
 

float f1_score = 4;

Parameters:

value - The f1Score to set.

Returns:

This builder for chaining.

clearF1Score

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearF1Score()

 Output only. The harmonic mean of recall and precision.
 

float f1_score = 4;

Returns:

This builder for chaining.

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;

Specified by:

getRecallAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The recallAt1.

setRecallAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setRecallAt1(float value)

 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;

Parameters:

value - The recallAt1 to set.

Returns:

This builder for chaining.

clearRecallAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearRecallAt1()

 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:

This builder for chaining.

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;

Specified by:

getPrecisionAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The precisionAt1.

setPrecisionAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setPrecisionAt1(float value)

 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;

Parameters:

value - The precisionAt1 to set.

Returns:

This builder for chaining.

clearPrecisionAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearPrecisionAt1()

 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:

This builder for chaining.

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;

Specified by:

getFalsePositiveRateAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The falsePositiveRateAt1.

setFalsePositiveRateAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setFalsePositiveRateAt1(float value)

 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;

Parameters:

value - The falsePositiveRateAt1 to set.

Returns:

This builder for chaining.

clearFalsePositiveRateAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearFalsePositiveRateAt1()

 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:

This builder for chaining.

getF1ScoreAt1

public float getF1ScoreAt1()

 Output only. The harmonic mean of [recall_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1].
 

float f1_score_at1 = 7;

Specified by:

getF1ScoreAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The f1ScoreAt1.

setF1ScoreAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setF1ScoreAt1(float value)

 Output only. The harmonic mean of [recall_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1].
 

float f1_score_at1 = 7;

Parameters:

value - The f1ScoreAt1 to set.

Returns:

This builder for chaining.

clearF1ScoreAt1

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearF1ScoreAt1()

 Output only. The harmonic mean of [recall_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry.precision_at1].
 

float f1_score_at1 = 7;

Returns:

This builder for chaining.

getTruePositiveCount

public long getTruePositiveCount()

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

int64 true_positive_count = 10;

Specified by:

getTruePositiveCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The truePositiveCount.

setTruePositiveCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setTruePositiveCount(long value)

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

int64 true_positive_count = 10;

Parameters:

value - The truePositiveCount to set.

Returns:

This builder for chaining.

clearTruePositiveCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearTruePositiveCount()

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

int64 true_positive_count = 10;

Returns:

This builder for chaining.

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;

Specified by:

getFalsePositiveCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The falsePositiveCount.

setFalsePositiveCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setFalsePositiveCount(long value)

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

int64 false_positive_count = 11;

Parameters:

value - The falsePositiveCount to set.

Returns:

This builder for chaining.

clearFalsePositiveCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearFalsePositiveCount()

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

int64 false_positive_count = 11;

Returns:

This builder for chaining.

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;

Specified by:

getFalseNegativeCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The falseNegativeCount.

setFalseNegativeCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setFalseNegativeCount(long value)

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

int64 false_negative_count = 12;

Parameters:

value - The falseNegativeCount to set.

Returns:

This builder for chaining.

clearFalseNegativeCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearFalseNegativeCount()

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

int64 false_negative_count = 12;

Returns:

This builder for chaining.

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;

Specified by:

getTrueNegativeCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

Returns:

The trueNegativeCount.

setTrueNegativeCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setTrueNegativeCount(long value)

 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;

Parameters:

value - The trueNegativeCount to set.

Returns:

This builder for chaining.

clearTrueNegativeCount

public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearTrueNegativeCount()

 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:

This builder for chaining.