[pymvpa] LinearSVM Classification Warning
Matthias Ekman
Matthias.Ekman at nf.mpg.de
Tue Feb 2 19:33:24 UTC 2010
wild guess :):
because you did some selection like:
ds = ds.selectSamples(N.array([l in [3,4] for l in ds.labels],dtype='bool'))
before training/testing?
May be you could post all relevant code parts?
btw, is there any reason why your data is not counterbalanced?
cheers,
Matthias
Geethmala wrote:
> Yes, but what is interesting is why is it not showing the warning for other
> labels? Why only 3?
>
> Thanks,
> Geethmala
>
> On Tue, Feb 2, 2010 at 2:19 PM, Matthias Ekman <Matthias.Ekman at nf.mpg.de>wrote:
>
>> Hi,
>>
>> i assume you already tracked the problem, right? ;-) ... since there a
>> no samples (of class 3) in chunk, 0, 4, 5... exactly what
>>
>>>>>> Classifier LinearCSVMC(kernel_type='linear', svm_impl='C_SVC')
>>>>>> wasn't trained to classify labels Set([3.0]) present in testing
>>>>>> dataset. Make sure that you have not mixed order/names of the
>>>>>> arguments anywhere
>> says.
>>
>> cheers,
>> Matthias
>>
>> Geethmala wrote:
>>> Here you go,
>>>
>>> Dataset / float32 153 x 40656
>>> uniq: 8 chunks 5 labels
>>> stats: mean=-0.0255406 std=0.994264 var=0.98856 min=-6.94855 max=6.71638
>>>
>>> Counts of labels in each chunk:
>>> chunks\labels 1.0 2.0 3.0 4.0 5.0
>>> --- --- --- --- ---
>>> 0.0 3 6 0 9 6
>>> 1.0 3 0 6 3 6
>>> 2.0 3 6 3 3 3
>>> 3.0 0 6 9 0 6
>>> 4.0 6 0 0 3 3
>>> 5.0 6 3 0 9 0
>>> 6.0 6 6 3 6 0
>>> 7.0 3 3 9 0 6
>>>
>>> Summary per label across chunks
>>> label mean std min max #chunks
>>> 1 3.75 1.98 0 6 7
>>> 2 3.75 2.49 0 6 6
>>> 3 3.75 3.6 0 9 5
>>> 4 4.12 3.33 0 9 6
>>> 5 3.75 2.49 0 6 6
>>>
>>> Summary per chunk across labels
>>> chunk mean std min max #labels
>>> 0 4.8 3.06 0 9 4
>>> 1 3.6 2.24 0 6 4
>>> 2 3.6 1.2 3 6 5
>>> 3 4.2 3.6 0 9 3
>>> 4 2.4 2.24 0 6 3
>>> 5 3.6 3.5 0 9 3
>>> 6 4.2 2.4 0 6 4
>>> 7 4.2 3.06 0 9 4
>>>
>>>
>>> Thanks,
>>> Geethmala
>>>
>>> On Tue, Feb 2, 2010 at 2:11 PM, Matthias Ekman <Matthias.Ekman at nf.mpg.de
>>> wrote:
>>>
>>>> Hi,
>>>>
>>>> could you please post:
>>>> print ds.summary()
>>>>
>>>> .. just to make sure, that there are samples belonging to class 3 :)
>>>>
>>>>
>>>> Matthias
>>>>
>>>> Geethmala wrote:
>>>>> No, I don't have a mix of them. They are all integer values.
>>>>>
>>>>> Thanks,
>>>>> Geethmala
>>>>>
>>>>> On Tue, Feb 2, 2010 at 1:59 PM, Yaroslav Halchenko <
>>>> debian at onerussian.com>wrote:
>>>>>> it means that
>>>>>>
>>>>>> Classifier LinearCSVMC(kernel_type='linear', svm_impl='C_SVC')
>>>>>> wasn't trained to classify labels Set([3.0]) present in testing
>>>>>> dataset. Make sure that you have not mixed order/names of the
>>>>>> arguments anywhere
>>>>>>
>>>>>> Also test if you don't have a mix of float and int labels in your
>>>>>> datasets (as I remember you are manually composing those).
>>>>>>
>>>>>>
>>>>>> On Tue, 02 Feb 2010, Geethmala wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>> I get the following warning when I run LinearCSVMC.
>>>>>>> WARNING: Classifier LinearCSVMC(kernel_type='linear',
>>>>>> svm_impl='C_SVC')
>>>>>>> wasn't trained to classify labels Set([3.0]) present in testing
>>>>>>> dataset. Make sure that you have not mixed order/names of the
>>>>>> arguments
>>>>>>> anywhere
>>>>>>> What does this warning mean?
>>>>>>> Thanks,
>>>>>>> Geethmala
>>>>>>> _______________________________________________
>>>>>>> Pkg-ExpPsy-PyMVPA mailing list
>>>>>>> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
>>>>>>> http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
>>>>>> --
>>>>>> .-.
>>>>>> =------------------------------ /v\ ----------------------------=
>>>>>> Keep in touch // \\ (yoh@|www.)onerussian.com
>>>>>> Yaroslav Halchenko /( )\ ICQ#: 60653192
>>>>>> Linux User ^^-^^ [175555]
>>>>>>
>>>>>>
>>>>>>
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