Gael - I tried separating out the lambda function into a standalone
function. Unfortunately no luck - same result :(.
Olivier - I'm using the default, which is n_jobs=1, so hopefully that
shouldn't be a problem.
The reason I'm using the threads is that I want to be able to train models
using a variety of different parameters that aren't actually parameters of
the classifier/regressor. These parameters involve feature construction
and things like that. I want to be able to train separate models testing
each of these parameters while making as much use of my 8 processors as I
can.
Previously when I was trying to use cross_val_score with n_jobs > 1, it
would always hang. Since then I think it has started working - I have no
clue why it's working now but wasn't before. I may simply go back to
trying that approach, though with 4 cv folds, I still won't be able to use
all 8 processors.
On Mon, Oct 6, 2014 at 8:39 AM, Gael Varoquaux <
[email protected]> wrote:
> > I'm trying to use cross_val_score inside a lambda function to take full
> > advantage of my processors -
>
> Try not using a lambda function, but a fully-feldged function. Parallel
> computing has problems with lambda functions.
>
> Gaël
>
>
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