Hi,
Meanwhile, on your data, could you confirm that there is some variance
in the obtained performances in a "good/lengthy" code, i.e. that values
np.std(distr_est.ca.dist_samples.samples[0], axis=1)
Thanks for the reply. Indeed, using a sphere_searchlight with the Monte
Carlo Testing, this gives me zeros only.
Hope this helps,
wolf
On 10/23/2012 10:08 PM, Yaroslav Halchenko wrote:
Thanks for the patience... unfortunately for now (after staring at the
code for a while in the evening and then having Aha moment outside) I
just disabled (it would throw an exception) providing any partitioners
which would change the targets in gnb or m1nn adhoc-searchlights. The
reason is simple - they were coded with an assumption of targets
being "constant" across partitioning schemes and that only partitions
would change... That is why you were getting the same values -- since
all values in the dist_samples were the same as the original
classification performance.
I will try to get into fixing it "properly" later today/tomorrow.
Meanwhile, on your data, could you confirm that there is some variance
in the obtained performances in a "good/lengthy" code, i.e. that values
np.std(distr_est.ca.dist_samples.samples[0], axis=1)
are not all 0s (or nearby)... either my testing dataset is too small or there
might be yet another bug hiding ;-)
On Mon, 22 Oct 2012, wolf zinke wrote:
Hi Yaroslav,
I hope you did survive the SfN well. If you have any ideas regarding
the constant value I get with my Monte Carlo testing of the
gnb_searchlight, I would be very happy. SO far I dod not try any
further to solve this issue, but tried a common Searchlight in
combination with Monte Carlo testing. And this takes an awful time
to get some results...
cheers,
wolf
On 10/11/2012 06:23 PM, Yaroslav Halchenko wrote:
On Thu, 11 Oct 2012, wolf zinke wrote:
Hi,
With some great input from Michael I figured out now, that contrary to the
common sphere_searchlight, the sphere_gnbsearchlight already implements a
sorry for being silent since I guess blame should be on me here:
sphere_gnbsearchlight and sphere_m1nnsearchlight indeed somewhat of a
crafty beasts to achieve super-fast performance with those "naive"
classification schemes -- they do splitting internally BUT should be
parametrized with a partitioner to be instructed on how to "split".
I will try looking in details of your case later on whenever rush of
preparation for sfn goes down... sorry about the delay
cheers
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