Quoting Mike Mascari <mascarm@mascari.com>:
> Quoting Hervé Piedvache <footcow@noos.fr>:
>
> >> Hi,
> >> Does anyone know a predictive or a database scoring solution for
> PostgreSQL
>
> in response, Marc A. Leith wrote:
>
> >Hmmmm, it's been a while since I did this but...
> >
> >Other tools do similar things - another was Knowledge Seeker from Angoss
> >Software - which built turnkey decision trees (this was fairly cheap
> depending
> >on the system it is running on). SAS also produced a turnkey modeling
> solution
> >(not cheap $$$$). You could also try SPSS (cheaper than SAS). Group 1
> Software
> >also marketed an all-in-one Modeling Sol'n - Model 1 (I think) but I never
> >actually used it.
> >
> >
> Would Joe Conway's PL/R procedural language be any help here? I'd guess
> there's an R package to fit the bill, but then again I'm only on page 30
> of Modern Applied Statistics in S-Plus. ;-)
>
> Mike Mascari
>
For a turnkey modeling solution, you need more than simple stat functions. These
solutions automatically transform or 'bucketize' the data and then analyze the
covariance between the score variables and the known result.
They then select a smaller number of variables and use them to build a model -
this may be done with a backward-propogation neural network, a more traditional
regression model, or some sort of decision tree or CHAID system. Model 1 uses 3
or 4 approaches and selects the 1 with the best (truest fit).
ModelMAX (and the like) have been honed over the last decade by teams of
statisticians and still generate models that are close but not yet equal to
those that our modeling team used to build. The difference was I could build a
model in a few hours (limited by the CPU on the PC) and they took several weeks
to hand tune the result.
Marc A. Leith
President
redboxdata inc.
E-mail:mleith@redboxdata.com