  One challenge impeding the analysis of terabyte scale x-ray scattering data
from the Linac Coherent Light Source LCLS, is determining the number of
clusters required for the execution of traditional clustering algorithms. Here
we demonstrate that previous work using bi-cross validation (BCV) to determine
the number of singular vectors directly maps to the spectral clustering problem
of estimating both the number of clusters and hyper parameter values. These
results indicate that the process of estimating the number of clusters should
not be divorced from the process of estimating other hyper parameters. Applying
this method to LCLS x-ray scattering data enables the identification of dropped
shots without manually setting boundaries on detector fluence and provides a
path towards identifying rare and anomalous events.
