public static final class ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder> implements ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder
Metrics for a single confidence threshold.Protobuf type
google.cloud.automl.v1.ClassificationEvaluationMetrics.ConfidenceMetricsEntrygetAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clone()
clone in interface com.google.protobuf.Message.Builderclone in interface com.google.protobuf.MessageLite.Builderclone in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface com.google.protobuf.Message.BuildersetField in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
clearField in interface com.google.protobuf.Message.BuilderclearField in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface com.google.protobuf.Message.BuilderclearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface com.google.protobuf.Message.BuildersetRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface com.google.protobuf.Message.BuilderaddRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(ClassificationEvaluationMetrics.ConfidenceMetricsEntry other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>IOExceptionpublic 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;getConfidenceThreshold in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The confidenceThreshold to set.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;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;getPositionThreshold in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The positionThreshold to set.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;public float getRecall()
Output only. Recall (True Positive Rate) for the given confidence threshold.
float recall = 2;getRecall in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setRecall(float value)
Output only. Recall (True Positive Rate) for the given confidence threshold.
float recall = 2;value - The recall to set.public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearRecall()
Output only. Recall (True Positive Rate) for the given confidence threshold.
float recall = 2;public float getPrecision()
Output only. Precision for the given confidence threshold.
float precision = 3;getPrecision in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setPrecision(float value)
Output only. Precision for the given confidence threshold.
float precision = 3;value - The precision to set.public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearPrecision()
Output only. Precision for the given confidence threshold.
float precision = 3;public float getFalsePositiveRate()
Output only. False Positive Rate for the given confidence threshold.
float false_positive_rate = 8;getFalsePositiveRate in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setFalsePositiveRate(float value)
Output only. False Positive Rate for the given confidence threshold.
float false_positive_rate = 8;value - The falsePositiveRate to set.public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearFalsePositiveRate()
Output only. False Positive Rate for the given confidence threshold.
float false_positive_rate = 8;public float getF1Score()
Output only. The harmonic mean of recall and precision.
float f1_score = 4;getF1Score in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setF1Score(float value)
Output only. The harmonic mean of recall and precision.
float f1_score = 4;value - The f1Score to set.public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearF1Score()
Output only. The harmonic mean of recall and precision.
float f1_score = 4;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;getRecallAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The recallAt1 to set.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;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;getPrecisionAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The precisionAt1 to set.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;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;getFalsePositiveRateAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The falsePositiveRateAt1 to set.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;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;getF1ScoreAt1 in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The f1ScoreAt1 to set.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;public long getTruePositiveCount()
Output only. The number of model created labels that match a ground truth label.
int64 true_positive_count = 10;getTruePositiveCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The truePositiveCount to set.public ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder clearTruePositiveCount()
Output only. The number of model created labels that match a ground truth label.
int64 true_positive_count = 10;public long getFalsePositiveCount()
Output only. The number of model created labels that do not match a ground truth label.
int64 false_positive_count = 11;getFalsePositiveCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The falsePositiveCount to set.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;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;getFalseNegativeCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The falseNegativeCount to set.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;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;getTrueNegativeCount in interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilderpublic 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;value - The trueNegativeCount to set.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;public final ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface com.google.protobuf.Message.BuildersetUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>public final ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface com.google.protobuf.Message.BuildermergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder>Copyright © 2025 Google LLC. All rights reserved.