[scikit-learn] Spherical Kmeans #OT

[Joel Nothman]

(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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>>
>
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