@Alex: I don't have a workaround for you but this seems like a useful
addition. I don't know how hard it would be, but you should definitely
raise it as an issue on the github issues page for the project:
https://github.com/scikit-learn/scikit-learn/issues?sort=updated&state=open
On Wed, Apr 24, 2013 at 7:06 AM, Alex Kopp <[email protected]> wrote:
> Hi,
>
> I am looking to build a random forest regression model with a pretty large
> amount of sparse data. I noticed that I cannot fit the random forest model
> with a sparse matrix. Unfortunately, a dense matrix is too large to fit in
> memory. What are my options?
>
> For reference, I have just over 400k features and just over 200k training
> examples
>
>
> ------------------------------------------------------------------------------
> Try New Relic Now & We'll Send You this Cool Shirt
> New Relic is the only SaaS-based application performance monitoring service
> that delivers powerful full stack analytics. Optimize and monitor your
> browser, app, & servers with just a few lines of code. Try New Relic
> and get this awesome Nerd Life shirt! http://p.sf.net/sfu/newrelic_d2d_apr
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
------------------------------------------------------------------------------
Try New Relic Now & We'll Send You this Cool Shirt
New Relic is the only SaaS-based application performance monitoring service
that delivers powerful full stack analytics. Optimize and monitor your
browser, app, & servers with just a few lines of code. Try New Relic
and get this awesome Nerd Life shirt! http://p.sf.net/sfu/newrelic_d2d_apr
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
