find_discords_rra: Finds a discord with RRA (Rare Rule Anomaly) algorithm....

In jMotif/jmotif-R: Time Series Analysis Toolkit Based on Symbolic Aggregate Discretization, i.e. SAX

Finds a discord with RRA (Rare Rule Anomaly) algorithm. Usually works the best with higher than that for HOT-SAX sizes of discretization parameters (i.e., PAA and Alphabet sizes).

Description

Finds a discord with RRA (Rare Rule Anomaly) algorithm. Usually works the best with higher than that for HOT-SAX sizes of discretization parameters (i.e., PAA and Alphabet sizes).

Usage

find_discords_rra(
  series,
  w_size,
  paa_size,
  a_size,
  nr_strategy,
  n_threshold,
  discords_num
)

Arguments

series	the input timeseries.
w_size	the sliding window size.
paa_size	the PAA size.
a_size	the alphabet size.
nr_strategy	the numerosity reduction strategy ("none", "exact", "mindist").
n_threshold	the normalization threshold.
discords_num	the number of discords to report.

References

Senin Pavel and Malinchik Sergey, SAX-VSM: Interpretable Time Series Classification Using SAX and Vector Space Model., Data Mining (ICDM), 2013 IEEE 13th International Conference on.

Examples

discords = find_discords_rra(ecg0606, 100, 4, 4, "none", 0.01, 1)
plot(ecg0606, type = "l", col = "cornflowerblue", main = "ECG 0606")
lines(x=c(discords[1,2]:(discords[1,2]+100)),
   y=ecg0606[discords[1,2]:(discords[1,2]+100)], col="red")

jMotif/jmotif-R documentation built on Sept. 27, 2022, 4:31 p.m.