Hallo Jamie,
thanks for the answer.
Yes, it is a little bit like grouping.
The main problem is that the data is continuous.
I created a mining model containing the columns to be watched.
For all columns I set the Content type to DISCRETIZED so the analysis server
tries to group
these columns. Afterwards I queried the model to find out wich case belongs
to which cluster.
The FAQ was very helpful for this task and together with BOL a solution was
found.
Now I can dive deeper into my data.
..
Thanks,
Lars
"Jamie MacLennan (MS)" <jamiemac.RemoveThis@online.microsoft.com> schrieb im
Newsbeitrag news:406320af$1@news.microsoft.com...
> This sounds like grouping, not clustering. If on the other hand, you want
> to automatically detect the clusters, you can create a mining model in
> Analysis Services using the clustering algorithm. You would set the
Cluster
> Count to 7 (in the model properties in the Mining Editor) and set the
Income
> property to input. You can either ignore all other columns, or set their
> values to "Predict Only."
>
> Afterwards you can run a query to determine which cluster each customer
was
> assigned - check out the FAQ at
> <a style='text-decoration: underline;' href="http://groups.msn.com/AnalysisServicesDataMining" target="_blank">http://groups.msn.com/AnalysisServicesDataMining</a> for details.
>
> --
>
> -Jamie MacLennan
> SQL Server Data Mining
> This posting is provided "AS IS" with no warranties, and confers no
rights.
> "Lars Roith" <lars.roith.RemoveThis@nospam.aitag.com> wrote in message
> news:%23VirZ3nEEHA.2272@TK2MSFTNGP09.phx.gbl...
> > Hello everybody,
> >
> > I have a relational database containign a table with a lot of facts
(e.g.
> > yearly income).
> > Now I want to build groups/clusters for the yearly income.
> > Is there a way to have the analysis services doing the job automtically?
> > The result should be:
> > e.g 7 Clusters with the following properties:
> > income between 0 and 20k
> > income between 20k and 30k
> > ...
> >
> > How can I achieve this.
> >
> > TIA,
> >
> > Lars
> >
> >
>
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