Compute Global-Local Outlier Score from Hierarchies. This is based
on hierarchical clustering where the minimum cluster size is k. The resulting
outlier score is a measure of how anomalous each observation is.
The function uses dbscan::hdbscan to do the calculation.
Arguments
- y
Numerical matrix or vector of data
- k
Minimum cluster size. Default: 5.
- ...
Additional arguments passed to
dbscan::hdbscan
See also
dbscan::glosh
Examples
y <- c(rnorm(49), 5)
glosh_scores(y)
#> [1] 0.22998175 0.13770592 0.00000000 0.50216476 0.10085345 0.21233471
#> [7] 0.81638234 0.50356211 0.24674124 0.34887395 0.40713836 0.63090402
#> [13] 0.10978182 0.84799465 0.29786450 0.37802907 0.00000000 0.37802907
#> [19] 0.09727780 0.21233471 0.70270996 0.12416389 0.23928860 0.46682546
#> [25] 0.11969442 0.37857913 0.47562942 0.67413352 0.28004749 0.41986011
#> [31] 0.32035853 0.41341344 0.00000000 0.36575737 0.17059295 0.54685774
#> [37] 0.44797990 0.00000000 0.27947906 0.16374192 0.71062970 0.46998476
#> [43] 0.05709659 0.27085566 0.10085345 0.83845358 0.17059295 0.44797990
#> [49] 0.33586203 0.95101224