108 citations · 248 across the 9 of their papers we have counts for
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cs.DB2020★ 3 cited
The Impact of Discretization Method on the Detection of Six Types of Anomalies in Datasets
Ralph Foorthuis
Anomaly detection is the process of identifying cases, or groups of cases, that are in some way unusual and do not fit the general patterns present in the dataset. Numerous algorit…
cs.DB2020★ 9 cited
SECODA: Segmentation- and Combination-Based Detection of Anomalies
Ralph Foorthuis
This study introduces SECODA, a novel general-purpose unsupervised non-parametric anomaly detection algorithm for datasets containing continuous and categorical attributes. The met…
cs.DB2020★ 108 cited
On the Nature and Types of Anomalies: A Review of Deviations in Data
Ralph Foorthuis
Anomalies are occurrences in a dataset that are in some way unusual and do not fit the general patterns. The concept of the anomaly is typically ill-defined and perceived as vague…