<s>
In	O
data	B-Application
mining	I-Application
,	O
cluster-weighted	B-General_Concept
modeling	I-General_Concept
(	O
CWM	O
)	O
is	O
an	O
algorithm-based	O
approach	O
to	O
non-linear	O
prediction	O
of	O
outputs	O
(	O
dependent	O
variables	O
)	O
from	O
inputs	O
(	O
independent	O
variables	O
)	O
based	O
on	O
density	B-General_Concept
estimation	I-General_Concept
using	O
a	O
set	O
of	O
models	O
(	O
clusters	O
)	O
that	O
are	O
each	O
notionally	O
appropriate	O
in	O
a	O
sub-region	O
of	O
the	O
input	O
space	O
.	O
</s>
<s>
The	O
procedure	O
for	O
cluster-weighted	B-General_Concept
modeling	I-General_Concept
of	O
an	O
input-output	O
problem	O
can	O
be	O
outlined	O
as	O
follows	O
.	O
</s>
<s>
In	O
the	O
same	O
way	O
as	O
for	O
regression	O
analysis	O
,	O
it	O
will	O
be	O
important	O
to	O
consider	O
preliminary	O
data	B-General_Concept
transformations	I-General_Concept
as	O
part	O
of	O
the	O
overall	O
modeling	O
strategy	O
if	O
the	O
core	O
components	O
of	O
the	O
model	O
are	O
to	O
be	O
simple	O
regression	O
models	O
for	O
the	O
cluster-wise	O
condition	O
densities	O
,	O
and	O
normal	O
distributions	O
for	O
the	O
cluster-weighting	O
densities	O
pj(x )	O
.	O
</s>
