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
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 ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstance()
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
newBuilder()
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilder()
newBuilder(ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilder(ClassificationEvaluationMetrics.ConfidenceMetricsEntry prototype)
parseDelimitedFrom(InputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseDelimitedFrom(InputStream input)
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
parseFrom(byte[] data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(byte[] data)
Parameter |
Name |
Description |
data |
byte[]
|
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
parseFrom(ByteString data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteString data)
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
parseFrom(CodedInputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(CodedInputStream input)
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
parseFrom(InputStream input)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(InputStream input)
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
parseFrom(ByteBuffer data)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteBuffer data)
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ClassificationEvaluationMetrics.ConfidenceMetricsEntry parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
parser()
public static Parser<ClassificationEvaluationMetrics.ConfidenceMetricsEntry> parser()
Methods
equals(Object obj)
public boolean equals(Object obj)
Parameter |
Name |
Description |
obj |
Object
|
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()
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()
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 ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder newBuilderForType()
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected 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 ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder toBuilder()
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Overrides