  We use a novel cluster identification tool StarGO to explore the metal poor
([Fe/H] $<$ -1.5) outer stellar halo (d $>$ 15 kpc) of the Milky Way using data
from Gaia, LAMOST and SDSS. Our method is built using an unsupervised learning
algorithm, a self-organizing map, which trains a 2-D neural network to learn
the topological structures of a data set from an n-D input space. Using a 4-D
space of angular momentum and orbital energy, we identify three distinct groups
corresponding to the Sagittarius, Orphan, and Cetus Streams. For the first time
we are able to discover a northern counterpart to the Cetus stream. We test the
robustness of this new detection using mock data and find that the significance
is more than 5-sigma. We also find that the existing southern counterpart
bifurcates into two clumps with different radial velocities. By exploiting the
visualization power of StarGO, we attach MW globular clusters to the same
trained neural network. The Sagittarius stream is found to have five related
clusters, confirming recent literature studies, and the Cetus stream has one
associated cluster, NGC 5824. This latter association has previously been
postulated, but can only now be truly confirmed thanks to the high-precision
Gaia proper motions and large numbers of stellar spectra from LAMOST. The large
metallicity dispersion of the stream indicates that the progenitor cannot be a
globular cluster. Given the mean metallicity of the stream, we propose that the
stream is the result of a merger of a low-mass dwarf galaxy that hosted a large
nuclear star cluster (NGC 5824).
