Google AutoML v1 API - Class ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry (3.2.0)

public sealed class ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry : IMessage<ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry>, IEquatable<ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry>, IDeepCloneable<ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry>, IBufferMessage, IMessage

Reference documentation and code samples for the Google AutoML v1 API class ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry.

Metrics for a single confidence threshold.

Inheritance

object > ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry

Implements

IMessage ClassificationEvaluationMetrics Types ConfidenceMetricsEntry, IEquatable ClassificationEvaluationMetrics Types ConfidenceMetricsEntry, IDeepCloneable ClassificationEvaluationMetrics Types ConfidenceMetricsEntry, IBufferMessage, IMessage

Inherited Members

object.GetHashCode()

object.GetType()

object.ToString()

Namespace

Google.Cloud.AutoML.V1

Assembly

Google.Cloud.AutoML.V1.dll

Constructors

ConfidenceMetricsEntry()

public ConfidenceMetricsEntry()

ConfidenceMetricsEntry(ConfidenceMetricsEntry)

public ConfidenceMetricsEntry(ClassificationEvaluationMetrics.Types.ConfidenceMetricsEntry other)

Parameter
Name	Description
`other`	`ClassificationEvaluationMetricsTypesConfidenceMetricsEntry`

Properties

ConfidenceThreshold

public float ConfidenceThreshold { get; set; }

Output only. Metrics are computed with an assumption that the model never returns predictions with score lower than this value.

Property Value
Type	Description
`float`

F1Score

public float F1Score { get; set; }

Output only. The harmonic mean of recall and precision.

Property Value
Type	Description
`float`

F1ScoreAt1

public float F1ScoreAt1 { get; set; }

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].

Property Value
Type	Description
`float`

FalseNegativeCount

public long FalseNegativeCount { get; set; }

Output only. The number of ground truth labels that are not matched by a model created label.

Property Value
Type	Description
`long`

FalsePositiveCount

public long FalsePositiveCount { get; set; }

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

Property Value
Type	Description
`long`

FalsePositiveRate

public float FalsePositiveRate { get; set; }

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

Property Value
Type	Description
`float`

FalsePositiveRateAt1

public float FalsePositiveRateAt1 { get; set; }

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.

Property Value
Type	Description
`float`

PositionThreshold

public int PositionThreshold { get; set; }

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.

Property Value
Type	Description
`int`

Precision

public float Precision { get; set; }

Output only. Precision for the given confidence threshold.

Property Value
Type	Description
`float`

PrecisionAt1

public float PrecisionAt1 { get; set; }

Output only. The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each example.

Property Value
Type	Description
`float`

Recall

public float Recall { get; set; }

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

Property Value
Type	Description
`float`

RecallAt1

public float RecallAt1 { get; set; }

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.

Property Value
Type	Description
`float`

TrueNegativeCount

public long TrueNegativeCount { get; set; }

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.

Property Value
Type	Description
`long`

TruePositiveCount

public long TruePositiveCount { get; set; }

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

Property Value
Type	Description
`long`