One efficient way of performing outlier detection in high-dimensional datasets is to use random forests. The isofor ‘isolates’ observations by randomly selecting a feature and then randomly selecting a split value between the maximum and minimum values of the selected feature.
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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