Re: using trainDocTopicModel to approximate p(topic|document)

[mw]

On 03/18/2015 05:54 PM, mw wrote:

Hello,

i am trying to use a topicmodel to approximate p(topic|document) like this

TopicModel model = new TopicModel(hadoopConf, conf.getEta(), conf.getAlpha(), dict trainingThreads, modelWeight,

                    models);

Vector docTopics = new DenseVector(new double[model.getNumTopics()]).assign(1.0/model.getNumTopics()); Matrix docTopicModel = new SparseRowMatrix(model.getNumTopics(), document.size());

int maxIters = 5000;
for(int i = 0; i < maxIters; i++) {
     model.trainDocTopicModel(document, docTopics, docTopicModel);
}

For some reason the values in docTopics dont change much.

E.g. the topicDistribution stays basically uniform...

Does that indicate that the current document does not fit into the model?
Could there be another explanation?

Best,
Max