Examples of FullAlchemyClassification

Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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  //For use in Corpus' getFullProfileCorpus(topicType) method
  public Document asLLDADocument(String topicType) {
    Set<String> topics = new HashSet<String>();
    //Note: if not LIWC or LIWCNB, we have no topics yet!
    if(topicType.equals("alchemy")) {
      FullAlchemyClassification fac = new FullAlchemyClassification(userID);
      int topTopics = 3;
      //alchemy too sparse to threshold
      int count = 0;
      for(String topic : fac.getCategorySet()) {
        if(count == topTopics) break; //stop getting more than 3 topics
        //if(fac.getScore(topic) < scoreThreshold) break; //stop getting low-prob topics
        topics.add(topic);
        count++;
      }
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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public class Diversity {
 
  private static Set<Double> diversitySet(String topicType, long uid) {
    Set<Double> valueSet = new HashSet<Double>();
    if(topicType.equals("alchemy")) {
      FullAlchemyClassification c = new FullAlchemyClassification(uid);
      for(String cat : c.getCategorySet()) {
        valueSet.add(c.getScore(cat));
      }
    } else if(topicType.equals("calais")) {
      FullCalaisClassification c = new FullCalaisClassification(uid);
      for(String cat : c.getCategorySet()) {
        valueSet.add(c.getScore(cat));
      }
    } else if(topicType.equals("textwise")) {
      FullCalaisClassification c = new FullCalaisClassification(uid);
      for(String cat : c.getCategorySet()) {
        valueSet.add(c.getScore(cat));
      }
    }
    return valueSet;
  }
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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          //get average cosine similarity to baseline
          double cosineSum = 0.0;
          int cosineCount = 0;
          for(Long uid : uids) {
            if(topicType.equals("alchemy")) {
              FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
              FullLLDAClassification llda = new FullLLDAClassification(topicType,alpha,false,reduction,uid);
              double sim = llda.cosineSimilarity(baseline);
              cosineSum += sim;
              cosineCount++;
            } else if(topicType.equals("calais")) {
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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          if(kCount == k) break;
          kCount++;
          lldaTopicSet.add(topic);
        }
        if(topicType.equals("alchemy")) {
          FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            kCount++;
            baselineTopicSet.add(topic);
          }
        } else if(topicType.equals("calais")) {
          FullCalaisClassification baseline = new FullCalaisClassification(uid);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            if(topic.equals("Other")) continue;
            kCount++;
            baselineTopicSet.add(topic);
          }
        } else if(topicType.equals("textwise")) {
          FullTextwiseClassification baseline = new FullTextwiseClassification(uid,true);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            kCount++;
            baselineTopicSet.add(topic);
          }
        }
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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          kCount++;
          svmTopicSet.add(topic);
          System.out.println("Adding topic "+topic+" "+svm.getScore(topic));
        }
        if(topicType.equals("alchemy")) {
          FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            kCount++;
            baselineTopicSet.add(topic);
          }
        } else if(topicType.equals("calais")) {
          FullCalaisClassification baseline = new FullCalaisClassification(uid);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            if(topic.equals("Other")) continue;
            kCount++;
            baselineTopicSet.add(topic);
          }
        } else if(topicType.equals("textwise")) {
          FullTextwiseClassification baseline = new FullTextwiseClassification(uid,true);
          kCount=0;
          for(String topic : baseline.getCategorySet()) {
            if(kCount == k) break;
            kCount++;
            baselineTopicSet.add(topic);
          }
        }
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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    for(String topic : Tools.getTopics(topicType)) {
      topicCounts.put(topic, 0);
    }
    for(Long uid : Tools.getCSVUserIDs()) {
      if(topicType.equals("alchemy")) {
        FullAlchemyClassification c = new FullAlchemyClassification(uid);
        if(c.getCategorySet().size() == 0) continue;
        String topTopic = c.getCategorySet().toArray(new String[1])[0];
        topicCounts.put(topTopic,topicCounts.get(topTopic)+1);
      } else if(topicType.equals("calais")) {
        FullCalaisClassification c = new FullCalaisClassification(uid);
        if(c.getCategorySet().size() == 0) continue;
        String topTopic = c.getCategorySet().toArray(new String[1])[0];
        if(topTopic.equals("Other") && c.getCategorySet().size() > 1)  topTopic = c.getCategorySet().toArray(new String[1])[1];
        else if(topTopic.equals("Other")) continue;
        topicCounts.put(topTopic,topicCounts.get(topTopic)+1);
      } else if(topicType.equals("textwise")) {
        FullTextwiseClassification c = new FullTextwiseClassification(uid,true);
        if(c.getCategorySet().size() == 0) continue;
        String topTopic = c.getCategorySet().toArray(new String[1])[0];
        topicCounts.put(topTopic,topicCounts.get(topTopic)+1);
      }
      count++;
    }
    double sum = 0.0;
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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        if(kCount == k) break;
        kCount++;
        lldaTopicSet.add(topic);
      }
      if(topicType.equals("alchemy")) {
        FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
        kCount=0;
        for(String topic : baseline.getCategorySet()) {
          if(kCount == k) break;
          kCount++;
          baselineTopicSet.add(topic);
        }
      } else if(topicType.equals("calais")) {
        FullCalaisClassification baseline = new FullCalaisClassification(uid);
        kCount=0;
        for(String topic : baseline.getCategorySet()) {
          if(kCount == k) break;
          if(topic.equals("Other")) continue;
          kCount++;
          baselineTopicSet.add(topic);
        }
      } else if(topicType.equals("textwise")) {
        FullTextwiseClassification baseline = new FullTextwiseClassification(uid,true);
        kCount=0;
        for(String topic : baseline.getCategorySet()) {
          if(kCount == k) break;
          kCount++;
          baselineTopicSet.add(topic);
        }
      }
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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    double cosineSum = 0.0;
    int cosineCount = 0;
    double squareSum = 0.0;
    for(Long uid : uids) {
      if(topicType.equals("alchemy")) {
        FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
        FullLLDAClassification inferred = new FullLLDAClassification(topicType,alpha,uid);
        double sim = inferred.cosineSimilarity(baseline);
        cosineSum += sim;
        squareSum += sim*sim;
        cosineCount++;
 
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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    double cosineSum = 0.0;
    int cosineCount = 0;
    double squareSum = 0.0;
    for(Long uid : uids) {
      if(topicType.equals("alchemy")) {
        FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
        FullLLDAClassification inferred = new FullLLDAClassification(topicType,alpha,uid);
        double sim = cosineKSimilarity(baseline,inferred,k);
        cosineSum += sim;
        squareSum += sim*sim;
        cosineCount++;
 
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Examples of uk.ac.cam.ha293.tweetlabel.classify.FullAlchemyClassification

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    double cosineSum = 0.0;
    int cosineCount = 0;
    double squareSum = 0.0;
    for(Long uid : uids) {
      if(topicType.equals("alchemy")) {
        FullAlchemyClassification baseline = new FullAlchemyClassification(uid);
        FullLLDAClassification inferred = new FullLLDAClassification(topicType,alpha,fewerProfiles,reduction,uid);
        if(inferred.getCategorySet().isEmpty()) continue;
        double sim = inferred.cosineSimilarity(baseline);
        cosineSum += sim;
        squareSum += sim*sim;
 
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