Package cz.zcu.fav.liks.ml.featuresel.validation

Examples of cz.zcu.fav.liks.ml.featuresel.validation.CrossValidator.multiValidate()

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      cv.multiValidate(features, trainer, 10, data, null, 0);

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

      print("POS tag");
      features.clear();
      features.add(new POSTagFeature(0, 5));
      cv.multiValidate(features, trainer, 10, data, null, 0);
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      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("POS tag");
      features.clear();
      features.add(new POSTagFeature(0, 5));
      cv.multiValidate(features, trainer, 10, data, null, 0);

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

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

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

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

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

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

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

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

      print("Specific bigram");
      features.clear();
      features.add(new SpecificBigramFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);
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      cv.multiValidate(features, trainer, 10, data, null, 0);

      print("Specific bigram");
      features.clear();
      features.add(new SpecificBigramFeature(0));
      cv.multiValidate(features, trainer, 10, data, null, 0);

    } catch (SQLException e) {
      e.printStackTrace();
    } catch (InvalidAttributeValueException e) {
      e.printStackTrace();
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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);
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        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));
        cv.multiValidate(features, trainer, 10, data, null, 0);
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        cv.multiValidate(features, trainer, 10, data, null, 0);

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

        print("Stopword threshold 10");
        features.clear();
        features.add(new StopwordFeature(10));
        cv.multiValidate(features, trainer, 10, data, null, 0);
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