You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@flink.apache.org by subash basnet <ya...@gmail.com> on 2016/03/01 17:07:06 UTC
Multi-dimensional[more than 2] input for KMeans Clustering in Apache flink
Hello all,
Currently I find only two-dimension input possible for the KMeans
Clustering in flink.
Is there any implementation already or what should be the approach to
implement
more than 2 dimensional input for KMeans in flink?
Or is there any other clustering method which taking more than two
dimensional data as input implemented in flink?
Best Regards,
Subash Basnet
Re: Multi-dimensional[more than 2] input for KMeans Clustering in
Apache flink
Posted by Fabian Hueske <fh...@gmail.com>.
Hi Subash,
the KMeans implementation in Flink is meant to be a simple toy example and
should not used for serious analysis tasks.
It shows how the DataSet API works by implementing a well-known algorithm.
Nonetheless, the example can be easily extended to work for three or more
dimensions.
You would need to adapt the methods to compute the distance and the
location of the new center.
Best, Fabian
2016-03-01 17:07 GMT+01:00 subash basnet <ya...@gmail.com>:
> Hello all,
>
> Currently I find only two-dimension input possible for the KMeans
> Clustering in flink.
>
> Is there any implementation already or what should be the approach to
> implement
> more than 2 dimensional input for KMeans in flink?
> Or is there any other clustering method which taking more than two
> dimensional data as input implemented in flink?
>
>
> Best Regards,
> Subash Basnet
>
Re: Multi-dimensional[more than 2] input for KMeans Clustering
inApache flink
Posted by subash basnet <ya...@gmail.com>.
Hello Fabian,
Thanks! Is KMeans only the clustering implementation currently existing in
flink.
Best Regards,
Subash Basnet
On Tue, Mar 1, 2016 at 5:22 PM, Fabian Hueske <fh...@gmail.com> wrote:
> [image: Boxbe] <https://www.boxbe.com/overview> This message is eligible
> for Automatic Cleanup! (fhueske@gmail.com) Add cleanup rule
> <https://www.boxbe.com/popup?url=https%3A%2F%2Fwww.boxbe.com%2Fcleanup%3Ftoken%3D4T%252Bhk%252FgptM9XU%252FFIj4RWV3KrW2HfYojxgJA5cZPZuDE6xubk2OiWSw7JXYYwsSvQQAhmFsmQFnjkP2FYJlMfftl85pIvki9DI1ufNJNf%252FJ%252BCfyroQbfxYDvCWlVoVnk61comf1RkXCs%253D%26key%3Ds5OSPv4B0vJOIKV19LQ55dwIZbAp7Pzkp9h1DRb%252F82E%253D&tc_serial=24567191674&tc_rand=504263425&utm_source=stf&utm_medium=email&utm_campaign=ANNO_CLEANUP_ADD&utm_content=001>
> | More info
> <http://blog.boxbe.com/general/boxbe-automatic-cleanup?tc_serial=24567191674&tc_rand=504263425&utm_source=stf&utm_medium=email&utm_campaign=ANNO_CLEANUP_ADD&utm_content=001>
>
> Hi Subash,
>
> the KMeans implementation in Flink is meant to be a simple toy example and
> should not used for serious analysis tasks.
> It shows how the DataSet API works by implementing a well-known algorithm.
>
> Nonetheless, the example can be easily extended to work for three or more
> dimensions.
> You would need to adapt the methods to compute the distance and the
> location of the new center.
>
> Best, Fabian
>
> 2016-03-01 17:07 GMT+01:00 subash basnet <ya...@gmail.com>:
>
>> Hello all,
>>
>> Currently I find only two-dimension input possible for the KMeans
>> Clustering in flink.
>>
>> Is there any implementation already or what should be the approach to
>> implement
>> more than 2 dimensional input for KMeans in flink?
>> Or is there any other clustering method which taking more than two
>> dimensional data as input implemented in flink?
>>
>>
>> Best Regards,
>> Subash Basnet
>>
>
>
>