<s>
The	O
algorithm	O
is	O
similar	O
to	O
the	O
k-means	B-Algorithm
algorithm	I-Algorithm
(	O
i.e.	O
</s>
<s>
Classification	B-General_Concept
is	O
a	O
procedure	O
that	O
classifies	O
an	O
input	O
signal	O
into	O
different	O
classes	O
.	O
</s>
<s>
Classification	B-General_Concept
algorithms	O
usually	O
require	O
a	O
supervised	O
learning	O
stage	O
.	O
</s>
<s>
In	O
the	O
classification	B-General_Concept
stage	O
,	O
a	O
new	O
observation	O
is	O
classified	O
into	O
a	O
class	O
by	O
using	O
the	O
characteristics	O
that	O
were	O
already	O
trained	O
.	O
</s>
<s>
k	O
q-flat	O
algorithm	O
can	O
be	O
used	O
for	O
classification	B-General_Concept
.	O
</s>
<s>
However	O
,	O
the	O
classification	B-General_Concept
performance	O
can	O
be	O
further	O
improved	O
if	O
we	O
impose	O
some	O
structure	O
on	O
the	O
flats	O
.	O
</s>
<s>
On	O
the	O
contrary	O
,	O
if	O
data	O
lies	O
in	O
a	O
very	O
high	O
dimension	O
space	O
but	O
near	O
a	O
common	O
center	O
,	O
then	O
k-means	B-Algorithm
algorithm	I-Algorithm
is	O
a	O
better	O
way	O
than	O
k	O
q-flat	O
algorithm	O
to	O
represent	O
the	O
data	O
.	O
</s>
<s>
If	O
A	O
is	O
the	O
identity	O
matrix	O
,	O
then	O
the	O
Mahalanobis	O
metric	O
is	O
exactly	O
the	O
same	O
as	O
the	O
error	O
measure	O
used	O
in	O
k-means	B-Algorithm
.	O
</s>
