Package cz.zcu.fav.liks.ml.featuresel.features.basic

Examples of cz.zcu.fav.liks.ml.featuresel.features.basic.StatementCountFeature


      // features.add(new AdverbReviewFeature(10));
      // features.add(new BigramFeature(10));
      // features.add(new WordPairFeature(10));
      // features.add(new LemmaFeature(10));
      features.add(new ThresholdFeature(0));
      features.add(new StatementCountFeature());
      // features.add(new StopwordReviewFeature(10));

      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();
      double weight = 0.1;
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    try {

      CrossValidator cv = new CrossValidator();
      List<Feature<Review>> features = new ArrayList<Feature<Review>>();
      features.add(new ThresholdFeature(0));
      features.add(new StatementCountFeature());

      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();
      List<Review> data = dataConn.getReviews();

      print("no selector");
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      print("Empty Feature");
      features.add(new EmptyFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Statement Count");
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Threshold 0");
      features.clear();
      features.add(new ThresholdFeature(0));
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      print("lemma + pos + statementcount");
      features.clear();
      features.add(new LemmaFeature(0));
      features.add(new POSTagFeature(0, 4));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + statementcount");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + pos");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new POSTagFeature(0, 4));
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + pos + statementcount");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new POSTagFeature(0, 4));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + bigrams");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new BigramFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + bigrams + statementcount");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new BigramFeature(0));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("words + pairs");
      features.clear();
      features.add(new ThresholdFeature(0));
      features.add(new WordPairFeature(10));
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Adjective + verb");
      features.clear();
      features.add(new AdjectiveFeature(0));
      features.add(new VerbFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Adjective + verb + statementcount");
      features.clear();
      features.add(new AdjectiveFeature(0));
      features.add(new VerbFeature(0));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("SpecificBigram + verb + adjectice + statementcount");
      features.clear();
      features.add(new SpecificBigramFeature(0));
      features.add(new VerbFeature(0));
      features.add(new AdjectiveFeature(0));
      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

    } catch (SQLException e) {
      e.printStackTrace();
    } catch (InvalidAttributeValueException e) {
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