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Posted to user@giraph.apache.org by Suijian Zhou <su...@gmail.com> on 2014/04/21 18:04:18 UTC
kmeans.
Hi,
Is there any example implementations of graph classification algorithms
in giraph? E.g, k-means, Bayes etc?
Best Regards,
Suijian
Re: kmeans.
Posted by Georgos Siganos <si...@gmail.com>.
Hi Suijian,
You can find an initial implementation of k-means in the following url. It
will be part of okapi at some point in the future.
https://github.com/vasia/okapi/blob/kmeans_aggregator_per_center/src/main/java/ml/grafos/okapi/kmeans
Cheers,
Georgos
2014-04-22 0:36 GMT+03:00 Suijian Zhou <su...@gmail.com>:
> Thanks Mirko, will try it.
>
> Best Regards,
> Suijian
>
>
>
>
>
> 2014-04-21 11:12 GMT-05:00 Mirko Kämpf <mi...@cloudera.com>:
>
> Hi Suijian,
>>
>> in Grafos.ml (which builds on Giraph as well) you find:
>>
>> Bayesian Personalized Ranking (BPR)
>>
>> - Overview <http://grafos.ml/okapi.html#tab13>
>> - Details <http://grafos.ml/okapi.html#tab14>
>> - How to Run <http://grafos.ml/okapi.html#tab15>
>> - References <http://grafos.ml/okapi.html#tab16>
>>
>> Bayesian Personalized Ranking from implicit feedback (BPR), the optimizes
>> Area Under the Curve (AUC) in a Collaborative Filtering setting. The
>> implementation in Okapi is a port of the myMediaLite implementation to the
>> giraph framework.
>>
>>
>>
>> k-Means clustering is also available in Mahout:
>>
>> https://mahout.apache.org/users/clustering/k-means-clustering.html
>>
>>
>>
>>
>>
>>
>>
>>
>> and in GraphLab you find:
>>
>>
>> KMeans++
>>
>> The kmeans program implements the KMeans++<http://en.wikipedia.org/wiki/K-means%2B%2B> algorithm
>> described by
>>
>> Arthur, D. and Vassilvitskii, S. (2007). "k-means++: the advantages of
>> careful seeding". Proceedings of the eighteenth annual ACM-SIAM symposium
>> on Discrete algorithms. pp. 1027–1035.
>>
>> http://docs.graphlab.org/clustering.html
>>
>>
>>
>>
>> On Mon, Apr 21, 2014 at 6:04 PM, Suijian Zhou <su...@gmail.com>wrote:
>>
>>> Hi,
>>> Is there any example implementations of graph classification
>>> algorithms in giraph? E.g, k-means, Bayes etc?
>>>
>>> Best Regards,
>>> Suijian
>>>
>>>
>>
>>
>> --
>> --
>> Mirko Kämpf
>> mirko@cloudera.com
>>
>>
>
Re: kmeans.
Posted by Suijian Zhou <su...@gmail.com>.
Thanks Mirko, will try it.
Best Regards,
Suijian
2014-04-21 11:12 GMT-05:00 Mirko Kämpf <mi...@cloudera.com>:
> Hi Suijian,
>
> in Grafos.ml (which builds on Giraph as well) you find:
>
> Bayesian Personalized Ranking (BPR)
>
> - Overview <http://grafos.ml/okapi.html#tab13>
> - Details <http://grafos.ml/okapi.html#tab14>
> - How to Run <http://grafos.ml/okapi.html#tab15>
> - References <http://grafos.ml/okapi.html#tab16>
>
> Bayesian Personalized Ranking from implicit feedback (BPR), the optimizes
> Area Under the Curve (AUC) in a Collaborative Filtering setting. The
> implementation in Okapi is a port of the myMediaLite implementation to the
> giraph framework.
>
>
>
> k-Means clustering is also available in Mahout:
>
> https://mahout.apache.org/users/clustering/k-means-clustering.html
>
>
>
>
>
>
>
>
> and in GraphLab you find:
>
>
> KMeans++
>
> The kmeans program implements the KMeans++<http://en.wikipedia.org/wiki/K-means%2B%2B> algorithm
> described by
>
> Arthur, D. and Vassilvitskii, S. (2007). "k-means++: the advantages of
> careful seeding". Proceedings of the eighteenth annual ACM-SIAM symposium
> on Discrete algorithms. pp. 1027–1035.
>
> http://docs.graphlab.org/clustering.html
>
>
>
>
> On Mon, Apr 21, 2014 at 6:04 PM, Suijian Zhou <su...@gmail.com>wrote:
>
>> Hi,
>> Is there any example implementations of graph classification algorithms
>> in giraph? E.g, k-means, Bayes etc?
>>
>> Best Regards,
>> Suijian
>>
>>
>
>
> --
> --
> Mirko Kämpf
> mirko@cloudera.com
>
>
Re: kmeans.
Posted by Mirko Kämpf <mi...@cloudera.com>.
Hi Suijian,
in Grafos.ml (which builds on Giraph as well) you find:
Bayesian Personalized Ranking (BPR)
- Overview <http://grafos.ml/okapi.html#tab13>
- Details <http://grafos.ml/okapi.html#tab14>
- How to Run <http://grafos.ml/okapi.html#tab15>
- References <http://grafos.ml/okapi.html#tab16>
Bayesian Personalized Ranking from implicit feedback (BPR), the optimizes
Area Under the Curve (AUC) in a Collaborative Filtering setting. The
implementation in Okapi is a port of the myMediaLite implementation to the
giraph framework.
k-Means clustering is also available in Mahout:
https://mahout.apache.org/users/clustering/k-means-clustering.html
and in GraphLab you find:
KMeans++
The kmeans program implements the
KMeans++<http://en.wikipedia.org/wiki/K-means%2B%2B> algorithm
described by
Arthur, D. and Vassilvitskii, S. (2007). "k-means++: the advantages of
careful seeding". Proceedings of the eighteenth annual ACM-SIAM symposium
on Discrete algorithms. pp. 1027-1035.
http://docs.graphlab.org/clustering.html
On Mon, Apr 21, 2014 at 6:04 PM, Suijian Zhou <su...@gmail.com>wrote:
> Hi,
> Is there any example implementations of graph classification algorithms
> in giraph? E.g, k-means, Bayes etc?
>
> Best Regards,
> Suijian
>
>
--
--
Mirko Kämpf
mirko@cloudera.com