Package cz.zcu.fav.liks.ml.classify.maxent

Examples of cz.zcu.fav.liks.ml.classify.maxent.MaxEntLBFGSTrainer

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        print("Naive bayes");
        SupervisedTrainer trainer = new NaiveBayesGaussianTrainer();
        cv.multiValidate(features, trainer, 10, data, null, 0);

        print("Maximum Entropy");
        trainer = new MaxEntLBFGSTrainer();
        cv.multiValidate(features, trainer, 10, data, null, 0);

        print("SVM");
        trainer = new MySVMTrainer();
        cv.multiValidate(features, trainer, 10, data, null, 0);
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      // 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;

      for (int i = 0; i < 10; i++)
        cv.multiValidate(features, trainer, 10, data, filter, weight * i);

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

      CrossValidator cv = new CrossValidator();
      List<Feature<Review>> features = new ArrayList<Feature<Review>>();
      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();

      List<Review> data = dataConn.getReviewsNo(20000);

      System.out.println("Datasize " + data.size());
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    try {

      CrossValidator cv = new CrossValidator();
      List<Feature<Review>> features = new ArrayList<Feature<Review>>();
      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();

      for (int i = 1; i < 20; i++) {

        List<Review> data = dataConn.getReviewsNo(1000 * i);
        System.out.println("Datasize " + data.size());
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    try {

      CrossValidator cv = new CrossValidator();
      List<Feature<Review>> features = new ArrayList<Feature<Review>>();
      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();

      List<Review> data = dataConn.getReviewsNo(20000);

      System.out.println("Datasize " + data.size());
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    try {

      CrossValidator cv = new CrossValidator();
      List<Feature<Review>> features = new ArrayList<Feature<Review>>();
      SupervisedTrainer trainer = new MaxEntLBFGSTrainer();

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

      print("Raw text");
      features.add(new ThresholdFeature(0));
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Related Classes of cz.zcu.fav.liks.ml.classify.maxent.MaxEntLBFGSTrainer

  • 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.Experiment4
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment5
  • cz.zcu.fav.liks.ml.featuresel.experiments.Experiment6
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