The Machine Learning “Advent Calendar” Day 8: Isolation Forest in Excel

Source: Towards Data Science

Isolation Forest

Isolation Forest may look technical, but its idea is simple: isolate points using random splits. If a point is isolated quickly, it is an anomaly; if it takes many splits, it is normal.

Using the tiny dataset 1, 2, 3, 9, we can see the logic clearly. We build several random trees, measure how many splits are needed to isolate each point, and then combine the results to compute an anomaly score. The fewer splits required, the higher the likelihood that the point is an outlier.