Hi Immanuel.
When I worked on that, I used hdf5 files. I think
it is the best way to communicate with mldata.
Maybe try h5py <http://h5py.alfven.org/docs-2.0/intro/quick.html>.
Documentation for the mldata interface is here <https://mldata.org/about/hdf5/>.

You should not include the training/test splits in the datasets, but rather
create a "task" for that. Including the training/test splits will mess
with the automatic conversions.

Hope that helps.

Cheers,
Andy

Am 13.06.2012 14:11, schrieb Immanuel B:
Hello,

I was going to upload some of the data sets listed here:
https://github.com/scikit-learn/scikit-learn/wiki/Setting-up-tests-to-benchmark-current-and-future-code
to mldata.org so make them easily available in scikit-learn.
The problem is that I can't find much information on  how mldata.org
parses the uploaded data or how to make data available in different
formats.
So I just uploaded the data in the supported RData format, but that
didn't do much good.

I also had a look at mldata-util (http://mloss.org/software/view/262/)
but couldn't find any useful documentation either.

Does someone know how to upload the data so that it can be retrieved
using fetch_mldata() ?

Thanks,
Immanuel

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