com.google.cloud.automl.v1

Interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

ClassificationEvaluationMetrics.ConfidenceMetricsEntry, ClassificationEvaluationMetrics.ConfidenceMetricsEntry.Builder

Enclosing class:

ClassificationEvaluationMetrics

public static interface ClassificationEvaluationMetrics.ConfidenceMetricsEntryOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
float	getConfidenceThreshold() Output only.
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.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

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

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getConfidenceThreshold

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:

The confidenceThreshold.

getPositionThreshold

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:

The positionThreshold.

getRecall

float getRecall()

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

float recall = 2;

Returns:

The recall.

getPrecision

float getPrecision()

 Output only. Precision for the given confidence threshold.
 

float precision = 3;

Returns:

The precision.

getFalsePositiveRate

float getFalsePositiveRate()

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

float false_positive_rate = 8;

Returns:

The falsePositiveRate.

getF1Score

float getF1Score()

 Output only. The harmonic mean of recall and precision.
 

float f1_score = 4;

Returns:

The f1Score.

getRecallAt1

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:

The recallAt1.

getPrecisionAt1

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:

The precisionAt1.

getFalsePositiveRateAt1

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:

The falsePositiveRateAt1.

getF1ScoreAt1

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;

Returns:

The f1ScoreAt1.

getTruePositiveCount

long getTruePositiveCount()

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

int64 true_positive_count = 10;

Returns:

The truePositiveCount.

getFalsePositiveCount

long getFalsePositiveCount()

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

int64 false_positive_count = 11;

Returns:

The falsePositiveCount.

getFalseNegativeCount

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:

The falseNegativeCount.

getTrueNegativeCount

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:

The trueNegativeCount.