How to use

weka.filters.unsupervised.instance.RemovePercentage

constructor

/** Creates a default RemovePercentage */
public Filter getFilter() {
 RemovePercentage f = new RemovePercentage();
 return f;
}

 /**
  * Main method for testing this class.
  * 
  * @param argv should contain arguments to the filter: use -h for help
  */
 public static void main(String[] argv) {
  runFilter(new RemovePercentage(), argv);
 }
}

 /**
  * Main method for testing this class.
  * 
  * @param argv should contain arguments to the filter: use -h for help
  */
 public static void main(String[] argv) {
  runFilter(new RemovePercentage(), argv);
 }
}

/** Creates a default RemovePercentage */
public Filter getFilter() {
 RemovePercentage f = new RemovePercentage();
 return f;
}

/**
 * Split the dataset into p% train an (100-p)% test set
 *
 * @param data Input data
 * @param p train percentage
 * @return Array of instances: (0) Train, (1) Test
 * @throws Exception Filterapplication went wrong
 */
public static Instances[] splitTrainVal(Instances data, double p) throws Exception {
 // Randomize data
 Randomize rand = new Randomize();
 rand.setInputFormat(data);
 rand.setRandomSeed(42);
 data = Filter.useFilter(data, rand);
 // Remove testpercentage from data to get the train set
 RemovePercentage rp = new RemovePercentage();
 rp.setInputFormat(data);
 rp.setPercentage(p);
 Instances train = Filter.useFilter(data, rp);
 // Remove trainpercentage from data to get the test set
 rp = new RemovePercentage();
 rp.setInputFormat(data);
 rp.setPercentage(p);
 rp.setInvertSelection(true);
 Instances test = Filter.useFilter(data, rp);
 return new Instances[]{train, test};
}

RemovePercentage rmvp = new RemovePercentage();
rmvp.setInvertSelection(true);
rmvp.setPercentage(Double.parseDouble(percentage));
Instances trainDataSet = Filter.useFilter(dataSet, rmvp);
rmvp = new RemovePercentage();
rmvp.setPercentage(Double.parseDouble(percentage));
rmvp.setInputFormat(dataSet);

@Override
protected void buildInternal(MultiLabelInstances trainingSet)
    throws Exception {
  Instances dataSet = new Instances(trainingSet.getDataSet());
  for (int i = 0; i < numOfModels; i++) {
    dataSet.randomize(rand);
    RemovePercentage rmvp = new RemovePercentage();
    rmvp.setInputFormat(dataSet);
    rmvp.setPercentage(percentage);
    rmvp.setInvertSelection(true);
    Instances trainDataSet = Filter.useFilter(dataSet, rmvp);
    MultiLabelInstances train = new MultiLabelInstances(trainDataSet, trainingSet.getLabelsMetaData());
    ensemble[i].build(train);
  }
}

RemovePercentage rmvp = new RemovePercentage();
rmvp.setInvertSelection(true);
rmvp.setPercentage(samplingPercentage);

/**
 * Split the dataset into p% train and (100-p)% testImdb set
 *
 * @param data Input data
 * @param p train percentage
 * @return Array of instances: (0) Train, (1) Test
 * @throws Exception Filterapplication went wrong
 */
public static Instances[] splitTrainTest(Instances data, double p) throws Exception {
 Randomize rand = new Randomize();
 rand.setInputFormat(data);
 rand.setRandomSeed(42);
 data = Filter.useFilter(data, rand);
 RemovePercentage rp = new RemovePercentage();
 rp.setInputFormat(data);
 rp.setPercentage(p);
 rp.setInvertSelection(true);
 Instances train = Filter.useFilter(data, rp);
 rp = new RemovePercentage();
 rp.setInputFormat(data);
 rp.setPercentage(p);
 Instances test = Filter.useFilter(data, rp);
 return new Instances[] {train, test};
}

RemovePercentage rp = new RemovePercentage();
rp.setPercentage(98);
rp.setInputFormat(data);

RemovePercentage rp = new RemovePercentage();
rp.setPercentage( m_RemovedPercentage );
rp.setInputFormat( dataSubSet );

for (Instance datum : generated) {
 final Instances rel = datum.relationalValue(0);
 RemovePercentage rp = new RemovePercentage();
 rp.setInputFormat(rel);
 rp.setPercentage(rand.nextDouble()*100);

RemovePercentage rp = new RemovePercentage();
rp.setPercentage(95);
rp.setInputFormat(data);

RemovePercentage rp = new RemovePercentage();
rp.setInputFormat(data);
rp.setPercentage(98);