public static final class ClassificationEvaluationMetrics.ConfidenceMetricsEntry extends GeneratedMessageV3 implements ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder
Metrics for a single confidence threshold.
Protobuf type
google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntry
Static Fields
CONFIDENCE_THRESHOLD_FIELD_NUMBER
public static final int CONFIDENCE_THRESHOLD_FIELD_NUMBER
Field Value
F1_SCORE_AT1_FIELD_NUMBER
public static final int F1_SCORE_AT1_FIELD_NUMBER
Field Value
F1_SCORE_FIELD_NUMBER
public static final int F1_SCORE_FIELD_NUMBER
Field Value
FALSE_NEGATIVE_COUNT_FIELD_NUMBER
public static final int FALSE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
FALSE_POSITIVE_COUNT_FIELD_NUMBER
public static final int FALSE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER
public static final int FALSE_POSITIVE_RATE_AT1_FIELD_NUMBER
Field Value
FALSE_POSITIVE_RATE_FIELD_NUMBER
public static final int FALSE_POSITIVE_RATE_FIELD_NUMBER
Field Value
POSITION_THRESHOLD_FIELD_NUMBER
public static final int POSITION_THRESHOLD_FIELD_NUMBER
Field Value
PRECISION_AT1_FIELD_NUMBER
public static final int PRECISION_AT1_FIELD_NUMBER
Field Value
PRECISION_FIELD_NUMBER
public static final int PRECISION_FIELD_NUMBER
Field Value
RECALL_AT1_FIELD_NUMBER
public static final int RECALL_AT1_FIELD_NUMBER
Field Value
RECALL_FIELD_NUMBER
public static final int RECALL_FIELD_NUMBER
Field Value
TRUE_NEGATIVE_COUNT_FIELD_NUMBER
public static final int TRUE_NEGATIVE_COUNT_FIELD_NUMBER
Field Value
TRUE_POSITIVE_COUNT_FIELD_NUMBER
public static final int TRUE_POSITIVE_COUNT_FIELD_NUMBER
Field Value
Static Methods
getDefaultInstance()
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstance()
Returns
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns
newBuilder()
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilder()
Returns
newBuilder(ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilder(ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
Parameter
Returns
parseDelimitedFrom(InputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseDelimitedFrom(InputStream input)
Parameter
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Exceptions
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
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Exceptions
parseFrom(byte[] data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(byte[] data)
Parameter
Name | Description |
data | byte[]
|
Returns
Exceptions
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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Exceptions
parseFrom(ByteString data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteString data)
Parameter
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Exceptions
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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Exceptions
parseFrom(CodedInputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(CodedInputStream input)
Parameter
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Exceptions
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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Exceptions
parseFrom(InputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(InputStream input)
Parameter
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Exceptions
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
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Exceptions
parseFrom(ByteBuffer data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteBuffer data)
Parameter
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Exceptions
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
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Exceptions
parser()
public static Parser<ClassificationEvaluationMetrics.ConfidenceMetricsEntry> parser()
Returns
Methods
equals(Object obj)
public boolean equals(Object obj)
Parameter
Returns
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 ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstanceForType()
Returns
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<ClassificationEvaluationMetrics.ConfidenceMetricsEntry> getParserForType()
Returns
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
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.
|
getUnknownFields()
public final UnknownFieldSet getUnknownFields()
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Overrides
hashCode()
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Overrides
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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Overrides
isInitialized()
public final boolean isInitialized()
Returns
Overrides
newBuilderForType()
public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilderForType()
Returns
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
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Overrides
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Returns
Overrides
toBuilder()
public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder toBuilder()
Returns
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Parameter
Overrides
Exceptions