MultiLabelClassificationMetrics

Declaration

struct MultiLabelClassificationMetrics<Label> where Label : Hashable

Topics

Creating the distribution

• init(_:strategy:)
• init(_:strategy:labels:)
• init(classifications:groundTruth:strategy:)
• init(classifications:groundTruth:strategy:labels:)
• init(confidenceThresholds:)
• MultiLabelClassificationMetrics.ThresholdSelectionStrategy

Getting the properties

• confidenceThresholds
• exampleCount
• labels
• meanAveragePrecision

Computing and scoring

• count(of:)
• f1Score(for:)
• falseNegativeCount(of:)
• falsePositiveCount(of:)
• precisionScore(for:)
• recallScore(for:)
• trueNegativeCount(of:)
• truePositiveCount(of:)

Updating the metrics

• add(_:)
• add(classifications:groundTruth:)

Computing the precision

• meanAveragePrecisionScore(_:)
• meanAveragePrecisionScore(_:labels:)
• meanAveragePrecisionScore(classifications:groundTruth:)
• meanAveragePrecisionScore(classifications:groundTruth:labels:)

Relationships

Conforms To

• Sendable
• SendableMetatype

See Also

Metrics

• Classification
• ClassificationDistribution
• ClassificationMetrics
• rootMeanSquaredError(_:)
• rootMeanSquaredError(_:_:)
• maximumAbsoluteError(_:)
• maximumAbsoluteError(_:_:)
• meanAbsoluteError(_:)
• meanAbsoluteError(_:_:)
• meanAbsolutePercentageError(_:)
• meanSquaredError(_:)
• meanSquaredError(_:_:)