[scikit-learn] Fwd: inconsistency between libsvm and scikit-learn.svc results

[Bill Ross]

One logical possibility is if svm would accept the scikit-learn changes.

On 8/27/16 6:42 AM, elgesto at gmail.com wrote:
> So there is no possibility to reach a consistency?
>
> 2016-08-27 15:36 GMT+03:00 olologin <olologin at gmail.com 
> <mailto:olologin at gmail.com>>:
>
>     On 08/27/2016 02:19 PM, elgesto at gmail.com
>     <mailto:elgesto at gmail.com> wrote:
>>     Can I update the libsvm version by myself?
>>
>>     2016-08-27 12:49 GMT+03:00 olologin <olologin at gmail.com
>>     <mailto:olologin at gmail.com>>:
>>
>>         On 08/27/2016 12:33 PM, elgesto at gmail.com
>>         <mailto:elgesto at gmail.com> wrote:
>>>
>>>         I have a project that is based on SVM algorithm implemented
>>>         by libsvm <https://www.csie.ntu.edu.tw/%7Ecjlin/libsvm/>.
>>>         Recently I decided to try several other classification
>>>         algorithm, this is where scikit-learn
>>>         <http://scikit-learn.org/> comes to the picture.
>>>
>>>         The connection to the scikit was pretty straightforward, it
>>>         supports libsvm format by |load_svmlight_file| routine. Ans
>>>         it's svm implementation is based on the same libsvm.
>>>
>>>         When everything was done, I decided to the check the
>>>         consistence of the results by directly running libsvm and
>>>         via scikit-learn, and the results were different. Among 18
>>>         measures in learning curves, 7 were different, and the
>>>         difference is located at the small steps of the learning
>>>         curve. The libsvm results seems much more stable, but
>>>         scikit-learn results have some drastic fluctuation.
>>>
>>>         The classifiers have exactly the same parameters of course.
>>>         I tried to check the version of libsvm in scikit-learn
>>>         implementation, but I din't find it, the only thing I found
>>>         was libsvm.so file.
>>>
>>>         Currently I am using libsvm 3.21 version, and scikit-learn
>>>         0.17.1 version.
>>>
>>>         I wound appreciate any help in addressing this issue.
>>>
>>>
>>>         |size libsvm scikit-learn 1 0.1336239435355727
>>>         0.1336239435355727 2 0.08699516468193455 0.08699516468193455
>>>         3 0.32928301642777424 0.2117238289550198 #different 4
>>>         0.2835688734876902 0.2835688734876902 5 0.27846766962743097
>>>         0.26651875338163966 #different 6 0.2853854654662907
>>>         0.18898048915599963 #different 7 0.28196058132165136
>>>         0.28196058132165136 8 0.31473956032575623 0.1958710201604552
>>>         #different 9 0.33588303670653136 0.2101641630182972
>>>         #different 10 0.4075242509025311 0.2997807499800962
>>>         #different 15 0.4391771087975972 0.4391771087975972 20
>>>         0.3837789445609818 0.2713167833345173 #different 25
>>>         0.4252154334940311 0.4252154334940311 30 0.4256407777477492
>>>         0.4256407777477492 35 0.45314944605858387
>>>         0.45314944605858387 40 0.4278633233755064 0.4278633233755064
>>>         45 0.46174762022239796 0.46174762022239796 50
>>>         0.45370452524846866 0.45370452524846866|
>>>
>>>
>>>
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>>>         https://mail.python.org/mailman/listinfo/scikit-learn
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>>
>>         This might be because current version of libsvm used in
>>         scikit is 3.10 from 2011. With some patch imported from
>>         upstream.
>>
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>>
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>
>     I don't think it is so easy, version which is used in scikit-learn
>     has many additional modifications.
>
>     from header of svm.cpp: /*    Modified 2010:    - Support for
>     dense data by Ming-Fang Weng    - Return indices for support
>     vectors, Fabian Pedregosa <fabian.pedregosa at inria.fr>
>     <mailto:fabian.pedregosa at inria.fr>    - Fixes to avoid name
>     collision, Fabian Pedregosa    - Add support for instance weights,
>     Fabian Pedregosa based on work      by Ming-Wei Chang, Hsuan-Tien
>     Lin, Ming-Hen Tsai, Chia-Hua Ho and      Hsiang-Fu Yu,
>     <http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances>
>     <http://www.csie.ntu.edu.tw/%7Ecjlin/libsvmtools/#weights_for_data_instances>.
>        - Make labels sorted in svm_group_classes, Fabian Pedregosa.  */
>
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