Index

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__init__() (pygarble.analysis.Analysis method) (pygarble.analysis.Signal method) (pygarble.analysis.Span method) (pygarble.detector.GarbleDetector method) (pygarble.ensemble.EnsembleDetector method)

A

Analysis (class in pygarble.analysis) analyze() (pygarble.detector.GarbleDetector method) (pygarble.ensemble.EnsembleDetector method)

applicable (pygarble.analysis.Signal attribute) applicable() (pygarble.detector.GarbleDetector method)

E

end (pygarble.analysis.Span attribute)

EnsembleDetector (class in pygarble.ensemble)

G

garbled (pygarble.analysis.Analysis attribute)

GarbleDetector (class in pygarble.detector)

M

model_version (pygarble.analysis.Analysis attribute)

P

predict() (pygarble.detector.GarbleDetector method) (pygarble.ensemble.EnsembleDetector method)

predict_proba() (pygarble.detector.GarbleDetector method) (pygarble.ensemble.EnsembleDetector method) profile (pygarble.analysis.Analysis attribute)

R

reason (pygarble.analysis.Signal attribute) (pygarble.analysis.Span attribute)

S

score (pygarble.analysis.Analysis attribute) (pygarble.analysis.Signal attribute) score() (pygarble.detector.GarbleDetector method) (pygarble.ensemble.EnsembleDetector method) Signal (class in pygarble.analysis) signals (pygarble.analysis.Analysis attribute)

Span (class in pygarble.analysis) spans (pygarble.analysis.Analysis property) (pygarble.analysis.Signal attribute) start (pygarble.analysis.Span attribute) status (pygarble.analysis.Analysis attribute) strategy (pygarble.analysis.Signal attribute)