har_eval: Evaluation of event detection

In harbinger: A Unified Time Series Event Detection Framework

Evaluation of event detection

Description

Hard evaluation of event detection producing confusion matrix and common metrics (accuracy, precision, recall, F1, etc.).

Usage

har_eval()

Value

har_eval object

References

• Harbinger documentation: https://cefet-rj-dal.github.io/harbinger

• Ogasawara, E., Salles, R., Porto, F., Pacitti, E. Event Detection in Time Series. 1st ed. Cham: Springer Nature Switzerland, 2025. doi:10.1007/978-3-031-75941-3

Examples

library(daltoolbox)

# Load anomaly example data
data(examples_anomalies)

dataset <- examples_anomalies$simple
head(dataset)

# Configure a change-point detector (GARCH)
model <- hcp_garch()

# Fit the detector
model <- fit(model, dataset$serie)

# Run detection
detection <- detect(model, dataset$serie)

# Show detected events
print(detection[(detection$event),])

# Evaluate detections
evaluation <- evaluate(har_eval(), detection$event, dataset$event)
print(evaluation$confMatrix)

# Plot the results
grf <- har_plot(model, dataset$serie, detection, dataset$event)
plot(grf)

harbinger documentation built on May 14, 2026, 5:06 p.m.