This script takes a list of datasets and transforms them into a suite of ground-truthed benchmarking datasets for anomaly detection. It depends on the library make-binary. These output datasets vary along the dimensions point difficulty, relative frequency of anomalies, and clusteredness. How these dimensions are discretized can be altered with the inputs difficulty-map, variance-map, and frequency-list. Please see the script readme for more details.
This script takes a list of datasets and transforms them into a suite of ground-truthed benchmarking datasets for anomaly detection. It depends on the library make-binary. These output datasets vary along the dimensions point difficulty, relative frequency of anomalies, and clusteredness. How these dimensions are discretized can be altered with the inputs difficulty-map, variance-map, and frequency-list. Please see the script readme for more details.
This script takes a list of datasets and transforms them into a suite of ground-truthed benchmarking datasets for anomaly detection. It depends on the library make-binary. These output datasets vary along the dimensions point difficulty, relative frequency of anomalies, and clusteredness. How these dimensions are discretized can be altered with the inputs difficulty-map, variance-map, and frequency-list. Please see the script readme for more details.
