We describe each node in the 4-HAP network by z(v) as described in Section 2.4. After dimensionality reduction via PCA, it was found that two principal components (PCs) express 98% of the data variance. PC0 takes up 79% of the data variance and PC1 19%. Due to the very high coverage of the data variance, we now describe each node with z'(v) composed of only two components, PC0 and PC1, see Section 2.4. Using the isolation forest algorithm as described in Section 2.5, we demonstrate separation of the outliers. A variety of contamination rates was tested, and a good fit was found by visual inspection. Figure shows the region of the data distribution where both normal and outlier nodes are present (split region) over PC0 and PC1 of z'(v). Normal species are depicted by red triangles, while blue circles represent the outliers. The aim was to find the best separation between the sparse and the dense regions of the data distribution.