[pymvpa] problem with high dimensional dataset

[Yaroslav Halchenko]

Hi Alok,

My guess is that you are using C=1 (or some other rigid value positive
value) and/or improperly scaled data... then libsvm's optimizer might
get into such loop.

For best troubleshooting provide

print mvpa.wtf()

print dataset.summary()
for your dataset which you try to process

and actual classifier you are using

On Mon, 22 Mar 2010, Alok Deshpande wrote:

>    Hi all,
>    I am currently working on basic classification problems on resting
>    state fMRI datasets (like gender differences, for example) The
>    dimensionality of feature vector is pretty large (128 time points X 33
>    X 64 X 64) I am working on a linux server with 8 cores and suff RAM.
>    Following is the output of command 'free -m'
>    free -m
>                 total       used       free     shared    buffers
>    cached
>    Mem:          8006       1254       6752          0        100
>    854
>    -/+ buffers/cache:        299       7706
>    Swap:        23454        209      23244
>    When I try to train a simple linear SVM classifier on the dataset (I
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