[pymvpa] Using ridge regression in a searchlight analysis
vincenttd at ucla.edu
Tue Jan 17 22:36:26 UTC 2017
I am trying to run a searchlight with a linear outcome ranging from 0 to 6
(I recoded the Targets of my dataset accordingly). I have 1 average pattern
for each of these target values for each of my 6 chunks (I should probably
include more trials instead of using averages, but this is what I am
playing with so far to have an even dataset) .
I thought of using ridge regression and here is the code I have so far:
clfsd = RidgeReg(lm=None, enable_ca=['stats'])
cv = CrossValidation(clfsd,
errorfx=lambda x,y: pearsonr(x,y),
sl = sphere_searchlight(cv, radius=3, postproc=mean_sample())
sl_results = sl(ds_alll)
I am having a hard time figuring out what the pearson r means in this
context. Is it the correlation between Y and Y-Hat? I end up with some
negative values. Any chance it could be interpreted has a negative relation
between the voxels within the searchlight and the continuous target values?
Also, since I am fairly new to pyMVPA, anyone has any suggestion on how to
figure that out by myself in the code? I tried running in debug mode but I
seem to run into an error that I don't have if I run the code normally.
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