Examples of cc.mallet.topics.TopicAssignment

cc.mallet.topics.TopicAssignment
This class combines a sequence of observed features with a sequence of hidden "labels".

        int topic = random.nextInt(numTopics);
        topics[position] = topic;
        
      }


      TopicAssignment t = new TopicAssignment(instance, topicSequence);
      data.add(t);
    }
    
    buildInitialTypeTopicCounts();
    initializeHistograms();

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    // Get counts of phrases
    for (int ti = 0; ti < numTopics; ti++)
      phrases[ti] = new gnu.trove.TObjectIntHashMap<String>();
    for (int di = 0; di < this.getData().size(); di++) {
      TopicAssignment t = this.getData().get(di);
      Instance instance = t.instance;
      FeatureSequence fvs = (FeatureSequence) instance.getData();
      boolean withBigrams = false;
      if (fvs instanceof FeatureSequenceWithBigrams) withBigrams = true;
      int prevtopic = -1;

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        int topic = random.nextInt(numTopics);
        topics[position] = topic;
        
      }


      TopicAssignment t = new TopicAssignment (instance, topicSequence);
      data.add (t);
    }
    
    buildInitialTypeTopicCounts();
    initializeHistograms();

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    // Get counts of phrases
    for (int ti = 0; ti < numTopics; ti++)
      phrases[ti] = new gnu.trove.TObjectIntHashMap<String>();
    for (int di = 0; di < this.getData().size(); di++) {
      TopicAssignment t = this.getData().get(di);
      Instance instance = t.instance;
      FeatureSequence fvs = (FeatureSequence) instance.getData();
      boolean withBigrams = false;
      if (fvs instanceof FeatureSequenceWithBigrams) withBigrams = true;
      int prevtopic = -1;

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        int topic = random.nextInt(numTopics);
        topics[position] = topic;
        
      }


      TopicAssignment t = new TopicAssignment (instance, topicSequence);
      data.add (t);
    }
    
    buildInitialTypeTopicCounts();
    initializeHistograms();

View Full Code Here

    
    // Get counts of phrases
    for (int ti = 0; ti < numTopics; ti++)
      phrases[ti] = new gnu.trove.TObjectIntHashMap<String>();
    for (int di = 0; di < this.getData().size(); di++) {
      TopicAssignment t = this.getData().get(di);
      Instance instance = t.instance;
      FeatureSequence fvs = (FeatureSequence) instance.getData();
      boolean withBigrams = false;
      if (fvs instanceof FeatureSequenceWithBigrams) withBigrams = true;
      int prevtopic = -1;

View Full Code Here

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Related Classes of cc.mallet.topics.TopicAssignment

cc.mallet.topics.ParallelTopicModel

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