Class GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics

Inheritance

object

GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics

Implements

IDirectResponseSchema

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Google.Apis.Aiplatform.v1.Data

Assembly: Google.Apis.Aiplatform.v1.dll

Syntax

public class GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics : IDirectResponseSchema

Properties

ConfidenceThreshold

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

Declaration

[JsonProperty("confidenceThreshold")]
public virtual float? ConfidenceThreshold { get; set; }

Property Value

Type	Description
float?

ConfusionMatrix

Confusion matrix of the evaluation for this confidence_threshold.

Declaration

[JsonProperty("confusionMatrix")]
public virtual GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix ConfusionMatrix { get; set; }

Property Value

Type	Description
GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
string

F1Score

The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score.

Declaration

[JsonProperty("f1Score")]
public virtual float? F1Score { get; set; }

Property Value

Type	Description
float?

F1ScoreAt1

The harmonic mean of recallAt1 and precisionAt1.

Declaration

[JsonProperty("f1ScoreAt1")]
public virtual float? F1ScoreAt1 { get; set; }

Property Value

Type	Description
float?

F1ScoreMacro

Macro-averaged F1 Score.

Declaration

[JsonProperty("f1ScoreMacro")]
public virtual float? F1ScoreMacro { get; set; }

Property Value

Type	Description
float?

F1ScoreMicro

Micro-averaged F1 Score.

Declaration

[JsonProperty("f1ScoreMicro")]
public virtual float? F1ScoreMicro { get; set; }

Property Value

Type	Description
float?

FalseNegativeCount

The number of ground truth labels that are not matched by a Model created label.

Declaration

[JsonProperty("falseNegativeCount")]
public virtual long? FalseNegativeCount { get; set; }

Property Value

Type	Description
long?

FalsePositiveCount

The number of Model created labels that do not match a ground truth label.

Declaration

[JsonProperty("falsePositiveCount")]
public virtual long? FalsePositiveCount { get; set; }

Property Value

Type	Description
long?

FalsePositiveRate

False Positive Rate for the given confidence threshold.

Declaration

[JsonProperty("falsePositiveRate")]
public virtual float? FalsePositiveRate { get; set; }

Property Value

Type	Description
float?

FalsePositiveRateAt1

The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.

Declaration

[JsonProperty("falsePositiveRateAt1")]
public virtual float? FalsePositiveRateAt1 { get; set; }

Property Value

Type	Description
float?

MaxPredictions

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 confidenceThreshold.

Declaration

[JsonProperty("maxPredictions")]
public virtual int? MaxPredictions { get; set; }

Property Value

Type	Description
int?

Precision

Precision for the given confidence threshold.

Declaration

[JsonProperty("precision")]
public virtual float? Precision { get; set; }

Property Value

Type	Description
float?

PrecisionAt1

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

Declaration

[JsonProperty("precisionAt1")]
public virtual float? PrecisionAt1 { get; set; }

Property Value

Type	Description
float?

Recall

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

Declaration

[JsonProperty("recall")]
public virtual float? Recall { get; set; }

Property Value

Type	Description
float?

RecallAt1

The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.

Declaration

[JsonProperty("recallAt1")]
public virtual float? RecallAt1 { get; set; }

Property Value

Type	Description
float?

TrueNegativeCount

The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.

Declaration

[JsonProperty("trueNegativeCount")]
public virtual long? TrueNegativeCount { get; set; }

Property Value

Type	Description
long?

TruePositiveCount

The number of Model created labels that match a ground truth label.

Declaration

[JsonProperty("truePositiveCount")]
public virtual long? TruePositiveCount { get; set; }

Property Value

Type	Description
long?

Implements

IDirectResponseSchema