[scikit-learn] Spherical Kmeans #OT

[Joel Nothman]

It may be useful in a pipeline if you need to normalise between a preceding
transformer and a following estimator.

On 28 June 2016 at 16:09, Michael Eickenberg <michael.eickenberg at gmail.com>
wrote:

> well, true :)
>
> but you can put it in pipelines! :)
>
> (so, in that logic, is there any reason for keeping it in the package?)
>
>
> On Tuesday, June 28, 2016, Joel Nothman <joel.nothman at gmail.com> wrote:
>
>> (Since Normalizer is applied to each sample independently, the
>> Pipeline/Transformer mechanism doesn't actually provide any benefit over
>> sklearn.preprocessing.normalize)
>>
>> On 28 June 2016 at 09:20, Michael Eickenberg <
>> michael.eickenberg at gmail.com> wrote:
>>
>>> You could do
>>>
>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.preprocessing import Normalizer
>>> from sklearn.cluster import KMeans   # (or e.g. MiniBatchKMeans)
>>>
>>> spherical_kmeans = make_pipeline(Normalizer(), KMeans(n_clusters=5))
>>>
>>>
>>>
>>> On Tue, Jun 28, 2016 at 12:28 AM, JAGANADH G <jaganadhg at gmail.com>
>>> wrote:
>>>
>>>> Hi Fred and Michel,
>>>>
>>>> Thanks for the reply . I think I git this and am able to run it.
>>>>
>>>>
>>>> Best
>>>> Jagan
>>>>
>>>>
>>>> On Mon, Jun 27, 2016 at 1:03 PM, Fred Mailhot <fred.mailhot at gmail.com>
>>>> wrote:
>>>>
>>>>> Per the example here:
>>>>>
>>>>>
>>>>> http://scikit-learn.org/stable/auto_examples/text/document_clustering.html
>>>>>
>>>>> if your inputs are normalized, sklearn's kmeans behaves like sperical
>>>>> kmeans (unless I'm misunderstanding something, which is certainly possible,
>>>>> caveat lector, &c )...
>>>>> On Jun 27, 2016 12:13 PM, "Michael Eickenberg" <
>>>>> michael.eickenberg at gmail.com> wrote:
>>>>>
>>>>>> hmm, not an answer, and off the top of my head:
>>>>>> if you normalize your data points to l2 norm equal 1, and then use
>>>>>> standard kmeans with euclidean distance (which then amounts to 2 - 2
>>>>>> cos(angle between points)) would this be enough for your purposes? (with a
>>>>>> bit of luck there may even be some sort of correspondence)
>>>>>>
>>>>>> Michael
>>>>>>
>>>>>> On Monday, June 27, 2016, JAGANADH G <jaganadhg at gmail.com> wrote:
>>>>>>
>>>>>>> Hi ,
>>>>>>> is there any Python package available for experiment with Sperical
>>>>>>> Kmeans ?
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> **********************************
>>>>>>> JAGANADH G
>>>>>>> http://jaganadhg.in
>>>>>>> *ILUGCBE*
>>>>>>> http://ilugcbe.org.in
>>>>>>>
>>>>>>
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>>>>>>
>>>>> _______________________________________________
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>>>>
>>>>
>>>> --
>>>> **********************************
>>>> JAGANADH G
>>>> http://jaganadhg.in
>>>> *ILUGCBE*
>>>> http://ilugcbe.org.in
>>>>
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