| stray {stray} | R Documentation |
stray: A package for robust anomaly detection in data streams with concept drift
Description
This package is a modification of HDoutliers package. HDoutliers is a powerful algorithm for the
detection of anomalous observations in a dataset, which has (among other advantages) the ability to detect
clusters of outliers in multi-dimensional data without requiring a model of the typical behavior of the system.
However, it suffers from some limitations that affect its accuracy. In this package, we propose solutions to
the limitations of HDoutliers, and propose an extension of the algorithm to deal with data streams that exhibit
non-stationary behavior. The results show that our proposed algorithm improves the accuracy, and enables the
trade-off between false positives and negatives to be better balanced.
Note
The name stray comes from Search and TRace AnomalY
References
Talagala, P. D., Hyndman, R. J., & Smith-Miles, K. (2019). Anomaly Detection in High Dimensional Data. https://www.monash.edu/business/ebs/research/publications/ebs/wp20-2019.pdf
Wilkinson, L. (2017). Visualizing big data outliers through distributed aggregation. IEEE transactions on visualization and computer graphics, 24(1), 256-266. https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf
See Also
The core functions in this package: find_HDoutliers,
display_HDoutliers
Full documentation and demos: