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
