I recreated it with some fake data, here's a short gist to show what I'm
talking about:
http://nbviewer.ipython.org/gist/choldgraf/6a7be7866f2a3a3d3f98
On Fri, Oct 10, 2014 at 1:29 PM, Chris Holdgraf
wrote:
> Yes - this is with the latest scikit-learn. Also, I'm using n_jobs==1, so
> there shou
On 2014-10-10 00:10, Benjamin Blumer wrote:
> Hi all,
>
> I see that gmm.score(x) returns the log probability of x for that
> point. I'm interested in integrating this probability over a region.
> For example, finding the probability of a ball being in the space
> (x,y,z) +/- (delta_x, delta_y, de
Yes - this is with the latest scikit-learn. Also, I'm using n_jobs==1, so
there shouldn't be any memmapping anyway, right?
Which version of scikit-learn? Have you tried with 0.15.2?
Your data should automatically get memory mapped to share some input
data with the 'n_jobs' worker processes.
--
Which version of scikit-learn? Have you tried with 0.15.2?
Your data should automatically get memory mapped to share some input
data with the 'n_jobs' worker processes.
--
Olivier
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Meet PCI DSS 3.0 Compliance Requirem
Hey all - I'm running into some memory issues with GridSearchCV and I
wonder if anyone can give an intuition as to why.
I'm cross-validating alpha parameters for Ridge regression. I'm trying 8
different parameters. My inputs are 2400x1900 (~370MB) in size.
When I run
%memit model.fit(X, y)
alo
