Hi, I have some graphs (in graphml format) for all the known categories whose nodes & edges have values and attributes associated with them. I want to do graph mining on this data so that whenever a new unknown graph comes in I can map it to the correct known category. After reading some stuff online I got to know about Mahout's Naive Bayesian algorithm. I am new to machine learning and I am trying to understand how this works. As far I understood from the description, this algorithm requires the input in Key, Value pairs. I am not sure on how can I convert this graph data (graphml) files into desired input format. Any suggestions?
Also any comments regarding other suitable algorithms/approaches are appreciated. Thanks in advance. -- View this message in context: http://lucene.472066.n3.nabble.com/Naive-Bayesian-How-to-convert-graphml-input-data-into-key-value-pairs-tp3997765.html Sent from the Mahout User List mailing list archive at Nabble.com.
