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Class ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry (2.78.0)
Version latestkeyboard_arrow_down
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
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
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 ()
getDescriptor()
public static final Descriptors . Descriptor getDescriptor ()
newBuilder()
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry . Builder newBuilder ()
newBuilder(ClassificationProto.ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry . Builder newBuilder ( ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry prototype )
parseDelimitedFrom(InputStream input)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseDelimitedFrom ( InputStream input )
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseDelimitedFrom ( InputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(byte[] data)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( byte [] data )
Parameter
Name Description
databyte []
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( byte [] data , ExtensionRegistryLite extensionRegistry )
parseFrom(ByteString data)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( ByteString data )
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( ByteString data , ExtensionRegistryLite extensionRegistry )
parseFrom(CodedInputStream input)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( CodedInputStream input )
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( CodedInputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(InputStream input)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( InputStream input )
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( InputStream input , ExtensionRegistryLite extensionRegistry )
parseFrom(ByteBuffer data)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( ByteBuffer data )
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry parseFrom ( ByteBuffer data , ExtensionRegistryLite extensionRegistry )
parser()
public static Parser<ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry > parser ()
Methods
equals(Object obj)
public boolean equals ( Object obj )
Parameter
Name Description
objObject
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 ()
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 ()
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()
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()
Returns
Type Description
int
Overrides
internalGetFieldAccessorTable()
protected GeneratedMessageV3 . FieldAccessorTable internalGetFieldAccessorTable ()
Overrides
isInitialized()
public final boolean isInitialized ()
Overrides
newBuilderForType()
public ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry . Builder newBuilderForType ()
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry . Builder newBuilderForType ( GeneratedMessageV3 . BuilderParent parent )
Overrides
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance ( GeneratedMessageV3 . UnusedPrivateParameter unused )
Returns
Type Description
Object
Overrides
toBuilder()
public ClassificationProto . ClassificationEvaluationMetrics . ConfidenceMetricsEntry . Builder toBuilder ()
writeTo(CodedOutputStream output)
public void writeTo ( CodedOutputStream output )
Overrides
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Last updated 2025-10-28 UTC.
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