Help interpreting outliers/anomalies when using Isolation Forest operator
Hi. I'm really liking the Isolation Forest operator under the Anomaly Detection Extension. Trees =100, Leaf Size =2, and average path as the score calculation gives me a result where the first 5 outliers match exactly with an R script using the Mahalanobis Distance function. That is great for comparisons. But is there a calculation or rule of thumb that you suggest for the Trees parameter? Or for cutoff score? Using my R script comparison I can easily match the 5 lowest scores. Score wise, is there a point or a calculation where outliers/anomalies end and the rest are not outliers? Thanks for any help.