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

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

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      // features.add(new VerbReviewFeature(10));
      // 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();
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      features.add(new StatementCountFeature());
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Threshold 0");
      features.clear();
      features.add(new ThresholdFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Lemma");
      features.clear();
      features.add(new LemmaFeature(0));
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        List<Review> data = dataConn.getReviewsNo(1000 * i);
        System.out.println("Datasize " + data.size());

        print("Raw text");
        features.add(new ThresholdFeature(0));
        cv.multiValidate(features, trainer, 10, data, null, 0);

        print("Threshold 10");
        features.clear();
        features.add(new ThresholdFeature(10));
        cv.multiValidate(features, trainer, 10, data, null, 0);

        print("Stopword");
        features.clear();
        features.add(new StopwordFeature(0));
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      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();
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      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();

      List<Review> data = dataConn.getReviewsNo(10000);

      print("Raw text");
      features.add(new ThresholdFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);
      System.out.println(features.get(0));

      print("Stopword");
      features.clear();
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Related Classes of cz.zcu.fav.liks.ml.featuresel.features.basic.ThresholdFeature

  • cz.zcu.fav.liks.ml.featuresel.data.Review
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment2
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment2a
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment3
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment3a
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment5
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment6
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