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 <suijian.z...@gmail.com>: > Thanks Mirko, will try it. > > Best Regards, > Suijian > > > > > > 2014-04-21 11:12 GMT-05:00 Mirko Kämpf <mirko.kae...@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 <suijian.z...@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 >> mi...@cloudera.com >> >> >
