View source: R/GetDetectorScore_GetNullAndPerfectScores.R
GetNullAndPerfectScores | R Documentation |
GetNullAndPerfectScores
Calculates the score of Perfect and Null
detectors scores. Perfect detector is one that outputs all true positives and no false
positives. And Null detector is one that outputs no anomaly detections.
GetNullAndPerfectScores(data)
data |
All dataset with training and test datasets and with at least |
This function calculates the scores based on three different profiles. Each tp, fp, tn, fn label is associated with a weight to give a more realistic score. For the standard profile weights are tp = 1, tn = 1, fp, = 0.11, and fn = 1. For the reward_low_FP_rate profile weights are tp = 1, tn = 1, fp, = 0.22, and fn = 1. For the reward_low_FN_rate profile weights are tp = 1, tn = 1, fp, = 0.11, and fn = 2.
data.frame with null and perfect detectors scores for each profile.
A. Lavin and S. Ahmad, “Evaluating Real-time Anomaly Detection Algorithms – the Numenta Anomaly Benchmark,” in 14th International Conference on Machine Learning and Applications (IEEE ICMLA’15), 2015.
## Generate data set.seed(100) n <- 180 x <- sample(1:100, n, replace = TRUE) x[70:90] <- sample(110:115, 21, replace = TRUE) x[25] <- 200 x[150] <- 170 df <- data.frame(timestamp = 1:n, value = x) # Add is.real.anomaly column df$is.real.anomaly <- 0 df[c(25,80,150), "is.real.anomaly"] <- 1 # Get null and perfect scores GetNullAndPerfectScores(df)
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