Evaluation of event detection using SoftED doi:10.48550/arXiv.2304.00439
Examples
library(daltoolbox)
#loading the example database
data(examples_anomalies)
#Using the simple
dataset <- examples_anomalies$simple
head(dataset)
#> serie event
#> 1 1.0000000 FALSE
#> 2 0.9689124 FALSE
#> 3 0.8775826 FALSE
#> 4 0.7316889 FALSE
#> 5 0.5403023 FALSE
#> 6 0.3153224 FALSE
# setting up time change point using GARCH
model <- hcp_garch()
# fitting the model
model <- fit(model, dataset$serie)
# making detections
detection <- detect(model, dataset$serie)
# filtering detected events
print(detection[(detection$event),])
#> idx event type
#> 51 51 TRUE changepoint
# evaluating the detections
evaluation <- evaluate(har_eval_soft(), detection$event, dataset$event)
print(evaluation$confMatrix)
#> event
#> detection TRUE FALSE
#> TRUE 0.93 0.07
#> FALSE 0.07 99.93
# ploting the results
grf <- har_plot(model, dataset$serie, detection, dataset$event)
plot(grf)
