<s>
A	O
latent	B-Algorithm
space	I-Algorithm
,	O
also	O
known	O
as	O
a	O
latent	B-Algorithm
feature	I-Algorithm
space	I-Algorithm
or	O
embedding	B-Algorithm
space	I-Algorithm
,	O
is	O
an	O
embedding	O
of	O
a	O
set	O
of	O
items	O
within	O
a	O
manifold	B-Architecture
in	O
which	O
items	O
resembling	O
each	O
other	O
are	O
positioned	O
closer	O
to	O
one	O
another	O
in	O
the	O
latent	B-Algorithm
space	I-Algorithm
.	O
</s>
<s>
Position	O
within	O
the	O
latent	B-Algorithm
space	I-Algorithm
can	O
be	O
viewed	O
as	O
being	O
defined	O
by	O
a	O
set	O
of	O
latent	O
variables	O
that	O
emerge	O
from	O
the	O
resemblances	O
from	O
the	O
objects	O
.	O
</s>
<s>
In	O
most	O
cases	O
,	O
the	O
dimensionality	O
of	O
the	O
latent	B-Algorithm
space	I-Algorithm
is	O
chosen	O
to	O
be	O
lower	O
than	O
the	O
dimensionality	O
of	O
the	O
feature	O
space	O
from	O
which	O
the	O
data	O
points	O
are	O
drawn	O
,	O
making	O
the	O
construction	O
of	O
a	O
latent	B-Algorithm
space	I-Algorithm
an	O
example	O
of	O
dimensionality	B-Algorithm
reduction	I-Algorithm
,	O
which	O
can	O
also	O
be	O
viewed	O
as	O
a	O
form	O
of	O
data	B-General_Concept
compression	I-General_Concept
.	O
</s>
<s>
Latent	B-Algorithm
spaces	I-Algorithm
are	O
usually	O
fit	O
via	O
machine	O
learning	O
,	O
and	O
they	O
can	O
then	O
be	O
used	O
as	O
feature	O
spaces	O
in	O
machine	O
learning	O
models	O
,	O
including	O
classifiers	O
and	O
other	O
supervised	O
predictors	O
.	O
</s>
<s>
The	O
interpretation	O
of	O
the	O
latent	B-Algorithm
spaces	I-Algorithm
of	O
machine	O
learning	O
models	O
is	O
an	O
active	O
field	O
of	O
study	O
,	O
but	O
latent	B-Algorithm
space	I-Algorithm
interpretation	O
is	O
difficult	O
to	O
achieve	O
.	O
</s>
<s>
Due	O
to	O
the	O
black-box	O
nature	O
of	O
machine	O
learning	O
models	O
,	O
the	O
latent	B-Algorithm
space	I-Algorithm
may	O
be	O
completely	O
unintuitive	O
.	O
</s>
<s>
Additionally	O
,	O
the	O
latent	B-Algorithm
space	I-Algorithm
may	O
be	O
high-dimensional	O
,	O
complex	O
,	O
and	O
nonlinear	O
,	O
which	O
may	O
add	O
to	O
the	O
difficulty	O
of	O
interpretation	O
.	O
</s>
<s>
Some	O
visualization	O
techniques	O
have	O
been	O
developed	O
to	O
connect	O
the	O
latent	B-Algorithm
space	I-Algorithm
to	O
the	O
visual	O
world	O
,	O
but	O
there	O
is	O
often	O
not	O
a	O
direct	O
connection	O
between	O
the	O
latent	B-Algorithm
space	I-Algorithm
interpretation	O
and	O
the	O
model	O
itself	O
.	O
</s>
<s>
Such	O
techniques	O
include	O
t-distributed	B-Algorithm
stochastic	I-Algorithm
neighbor	I-Algorithm
embedding	I-Algorithm
(	O
t-SNE	B-Algorithm
)	O
,	O
where	O
the	O
latent	B-Algorithm
space	I-Algorithm
is	O
mapped	O
to	O
two	O
dimensions	O
for	O
visualization	O
.	O
</s>
<s>
Latent	B-Algorithm
space	I-Algorithm
distances	O
lack	O
physical	O
units	O
,	O
so	O
the	O
interpretation	O
of	O
these	O
distances	O
may	O
depend	O
on	O
the	O
application	O
.	O
</s>
<s>
A	O
number	O
of	O
algorithms	O
exist	O
to	O
create	O
latent	B-Algorithm
space	I-Algorithm
embeddings	O
given	O
a	O
set	O
of	O
data	O
items	O
and	O
a	O
similarity	O
function	O
.	O
</s>
