hmu_pca: Multivariate anomaly detector using PCA

In harbinger: A Unified Time Series Event Detection Framework

Multivariate anomaly detector using PCA

Description

Multivariate anomaly detector using PCA doi:10.1016/0098-3004(93)90090-R

Usage

hmu_pca()

Value

hmu_pca object

Examples

library(daltoolbox)

#loading the example database
data(examples_harbinger)

#Using the time series 9
dataset <- examples_harbinger$multidimensional
head(dataset)

# establishing hmu_pca method
model <- hmu_pca()

# fitting the model using the two columns of the dataset
model <- fit(model, dataset[,1:2])

# making detections
detection <- detect(model, dataset[,1:2])

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

# evaluating the detections
evaluation <- evaluate(model, detection$event, dataset$event)
print(evaluation$confMatrix)

harbinger documentation built on June 22, 2024, 7:38 p.m.