<s>
The	O
U-matrix	B-Algorithm
(	O
unified	O
distance	O
matrix	O
)	O
is	O
a	O
representation	O
of	O
a	O
self-organizing	B-Algorithm
map	I-Algorithm
(	O
SOM	O
)	O
where	O
the	O
Euclidean	O
distance	O
between	O
the	O
codebook	B-Algorithm
vectors	I-Algorithm
of	O
neighboring	O
neurons	B-Architecture
is	O
depicted	O
in	O
a	O
grayscale	O
image	O
.	O
</s>
<s>
If	O
the	O
map	O
is	O
twist-free	O
,	O
the	O
distance	O
between	O
the	O
codebook	B-Algorithm
vectors	I-Algorithm
of	O
neighboring	O
neurons	B-Architecture
gives	O
an	O
approximation	O
of	O
the	O
distance	O
between	O
different	O
parts	O
of	O
the	O
underlying	O
data	O
.	O
</s>
<s>
When	O
such	O
distances	O
are	O
depicted	O
in	O
a	O
grayscale	O
image	O
,	O
light	O
colors	O
depict	O
closely	O
spaced	O
node	O
codebook	B-Algorithm
vectors	I-Algorithm
and	O
darker	O
colors	O
indicate	O
more	O
widely	O
separated	O
node	O
codebook	B-Algorithm
vectors	I-Algorithm
.	O
</s>
<s>
Thus	O
,	O
groups	O
of	O
light	O
colors	O
can	O
be	O
considered	O
as	O
clusters	B-Algorithm
,	O
and	O
the	O
dark	O
parts	O
as	O
the	O
boundaries	O
between	O
the	O
clusters	B-Algorithm
.	O
</s>
<s>
This	O
representation	O
can	O
help	O
to	O
visualize	O
the	O
clusters	B-Algorithm
in	O
the	O
high-dimensional	O
spaces	O
,	O
or	O
to	O
automatically	O
recognize	O
them	O
using	O
relatively	O
simple	O
image	B-Algorithm
processing	I-Algorithm
techniques	O
.	O
</s>
