underpredict the total number of galaxies by $\sim6\%$ and for kNN we underpredict by $\sim3\%$. These are both small and do not appear to significantly alter the correlation function shown in Figure \[fig:milxi\] at scales relevant to large-scale structure analyses. At these scales, the correlation function is dominated by the 2-halo term which comes mostly from halos containing a single galaxy. As discussed above, such halos are the most abundant by far. In addition, Figure \[fig:mildist\] indicates that the number of halos we predict with $N_{gal}=1$ matches the true distribution reasonably well. Hence, it is not surprising that our predicted $\xi(r)$ is in fair agreement with the true $\xi(r)$ at large $r$.

We can also look at the distribution of $N_{gal}$ as a function of the various features. Figure \[fig:milfeat\] shows this in scatter plot form for the kNN test. The analogous plots for SVM are largely the same. Here we have randomly subsampled the number of points plotted to 3,000. The black points show true $N_{gal}$ versus features while the red points show predicted $N_{gal}$. One can see that overall the span of the points overlaps quite well between the true and predicted sets, again indicating the general statistical 