Examples of anomalies modified from Chandola et al. 2009
Anomalies are data examples that are, simply put, weird. They are far from typical data points and make us wonder if they are not generated by a completely different process. I am interested in them as a mechanism for scientific discovery: weird, anomalous examples test and often break our current theories.
Combination Random Cut Forest
Robust random cut forests and isolation forests are two approaches to detecting anomalies in data. Since they are related models, I provide a combined code base that allows one to use them in conjunction. See the GitHub repo for more details. A description of the ideas is found in the associated write-up.
An example Combination Random Cut Tree.