Re: [pymvpa] Fwd: Searchlight Accuracy Decimal Precision Issue

[Tyler Adkins]

Below is the output of data.summary() for one subject:

Dataset: 211x260502@float32, , , 
stats: mean=-0.0847961 std=0.967814 var=0.936665 min=-22.0178 max=24.7773
No details due to large number of targets or chunks. Increase maxc and maxt
if desired
Summary for targets across chunks
  targets  mean std min max #chunks
0 0.502 0.5  0   1106
1 0.498 0.5  0   1105
Sequence statistics for 211 entries from set [0, 1]
Counter-balance table for orders up to 2:
Targets/Order  O1  |   O2  |
  0:   0  105  |  105  0   |
  1:  105  0   |   0  104  |
Correlations: min=-0.99 max=0.98 mean=-0.0048 sum(abs)=1e+02


On Thu, May 17, 2018 at 7:21 AM, Yaroslav Halchenko 
wrote:

> Please share output of
>
> print data.summary()
>
> Right before your give it to searchlight
>
>
> On May 17, 2018 3:59:39 AM EDT, Tyler Adkins  wrote:
>>
>> Hello,
>>
>> I am running a searchlight analysis and I encountered a strange feature
>> of the resulting classification accuracies. All of the non-zero accuracies
>> have only one decimal point of precision (e.g., .5, .6., .7., .8, etc.).
>> Unfortunately, I'm not able to figure out what aspect of my code is leading
>> to this truncating or rounding of the accuracies.
>>
>> I attached my code below, but here's some information about my analysis.
>> Please let me know if you would like me to provide any other information
>> about the analysis. My searchlight repeats a 10-fold cross-validation
>> procedure for a linear support vector classifier with default parameters.
>> The number of classes is 2 and the total number of samples is roughly 240.
>> The sequence of samples is randomized and balanced so that there is an
>> equal number of instances of the two classes in each of the 10 folds. The
>> searchlight also applies the mean_sample() postproc so that the resulting
>> classification accuracies are averaged over the cross-validation folds.
>>
>> As mentioned above, I'm unsure what about my script is leading to the
>> rounding/truncating of the accuracies. Most of the script is copied from
>> one of the PyMVPA searchlight tutorials, which further adds to my
>> confusion, since the tutorial searchlight clearly outputs accuracies with
>> greater than 1-decimal precision. ​
>> I would greatly appreciate any ideas you might have about what could be
>> causing this problem or how to address it.
>>
>>
>> Thank you for your time.
>>
>> Best,
>>
>>
>> Tyler Adkins
>> PhD Pre-candidate | Cognition and Cognitive Neuroscience
>> University of Michigan Department of Psychology
>> 530 Church Street Ann Arbor, MI 48109
>> 
>> -1043
>> Email: adkin...@umich.edu
>> Office: 3036 East Hall
>> Lab: B018 East Hall
>>
>>
>>
> --
> Sent from a phone which beats iPhone.
>
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[pymvpa] Fwd: Searchlight Accuracy Decimal Precision Issue

[Tyler Adkins]

Hello,

I am running a searchlight analysis and I encountered a strange feature of the 
resulting classification accuracies. All of the non-zero accuracies have only 
one decimal point of precision (e.g., .5, .6., .7., .8, etc.). Unfortunately, 
I'm not able to figure out what aspect of my code is leading to this truncating 
or rounding of the accuracies.

I attached my code below, but here's some information about my analysis. Please 
let me know if you would like me to provide any other information about the 
analysis. My searchlight repeats a 10-fold cross-validation procedure for a 
linear support vector classifier with default parameters. The number of classes 
is 2 and the total number of samples is roughly 240. The sequence of samples is 
randomized and balanced so that there is an equal number of instances of the 
two classes in each of the 10 folds. The searchlight also applies the 
mean_sample() postproc so that the resulting classification accuracies are 
averaged over the cross-validation folds.

As mentioned above, I'm unsure what about my script is leading to the 
rounding/truncating of the accuracies. Most of the script is copied from one of 
the PyMVPA searchlight tutorials, which further adds to my confusion, since the 
tutorial searchlight clearly outputs accuracies with greater than 1-decimal 
precision.
I would greatly appreciate any ideas you might have about what could be causing 
this problem or how to address it.


Thank you for your time.

Best,


Tyler Adkins
PhD Pre-candidate | Cognition and Cognitive Neuroscience
University of Michigan Department of Psychology
530 Church Street Ann Arbor, MI 48109-1043
Email: adkin...@umich.edu
Office: 3036 East Hall
Lab: B018 East Hall
>


pymvpa_searchlight.py
Description: Binary data
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