Only 1 of the variants can be found in the litterature (with corrects 
parameters) as the random (ensemble) classifier chain.
Other variants can not be found in the litterature, but I used them to 
compare several order strategies for my thesis, and thus will probably 
be removed if it is integrated as they have no citation and are too recent.

Should I then begin to further improve the classifier chain to make it 
closer to the litterature (removing the variants, eventually removing 
the flexibility concerning the steps, ...)? And rakel?

> I think classifier chains would be a nice addition.
> I am not very familiar with the different variants you implemented, though.
>
>
> On 07/10/2015 09:32 AM, Al wrote:
>> I should probably have put a link to the current implementation as it is
>> now. The link to this project (purged, i removed the various things from
>> my thesis) is:
>>
>> https://github.com/Al-Pena/ClassifierChain
>>
>>> 2015-07-10 15:20 GMT+02:00 Al <alain.pen...@gmail.com>:
>>>> My name is Alain Pena, (now previously) student in computer engineering
>>>> at University of Liège.
>>>> For my master thesis, I had to implement some methods for multilabel
>>>> classification, those methods being RAKEL [1] and (Ensemble) Classifier
>>>> Chain [2], as well as some variants of this latter (order of the chain
>>>> or length of its links for example).
>>>>
>>>> They are currently lazy (I had a problem with memory while doing my
>>>> thesis, so I had to implement them lazily, throwing each estimator away)
>>>> as well as single threaded. They are tested for multilabel only with a
>>>> test coverage of about 80%.
>>>>
>>>> Before eventually upgrading them to make them more robust and versatile,
>>>> I wondered if scikit-learn would have any interest in those methods.
>>> I've used a (hacky) homegrown RAKEL with some success [1], and I'm
>>> interested to see the code and maybe get it in sklearn eventually.
>>> Publishing as a separate project or a bunch of gists [2] would be a
>>> good idea. I never used classifier chains, but I know the idea.
>>>
>>> [1] 
>>> https://staff.fnwi.uva.nl/m.derijke/wp-content/papercite-data/pdf/buitinck-multi-emotion-2015.pdf
>>> [2] https://gist.github.com
>>>
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