 One of the main problems of the application of iForest to anomaly detection was not with the model itself, but rather in the way the “anomaly score” was computed.This problem was highlighted by Sahand Hariri, Matias Carrasco Kind and Robert J. Brunner in a 2018 paper, wherein they proposed an improved iForest model named "Extended Isolation Forest" (EIF).In the same paper the authors describe the improvements made to the original model and how they are able to enhance the consistency and reliability of the anomaly score produced for a given data point.