Sets some points as pre-defined landmarks with respect to which distances and/or isolation kernel values will be calculated for arbitrary new points in calls to `predict` with types `"dist"`, `"avg_sep"`, `"kernel"`. If any points have already been set as references in the model object, they will be overwritten with the new points passed here.
Be aware that adding reference points requires building a tree indexer.
isotree.set.reference.points(model, data, with_distances = FALSE)The same `model` object (as invisible), but now with added reference points that can be used for new distance and/or kernel calculations with respect to other arbitrary points.
An Isolation Forest model (as returned by function isolation.forest) for which reference points for distance and/or kernel calculations will be set.
The object will be modified in-place.
Observations to set as reference points for future distance and/or isolation kernel calculations. Same format as for predict.isolation_forest.
Whether to pre-calculate node distances (this is required to calculate distance from arbitrary points to the reference points).
Note that reference points for distances can only be set when using `assume_full_distr=FALSE` (which is the default).
Note that points are added in terms of their terminal node indices, but the raw data about them is not kept - thus, calling isotree.add.tree later on a model with reference points requires passing those reference points again to add their node indices to the new tree.
isotree.build.indexer