How to use

setPercentage

method

in

weka.filters.unsupervised.instance.RemovePercentage

 setPercentage(Double.parseDouble(percent));
} else {
 setPercentage(50.0);

 setPercentage(Double.parseDouble(percent));
} else {
 setPercentage(50.0);

/**
 * 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));
rmvp.setInputFormat(dataSet);
Instances trainDataSet = Filter.useFilter(dataSet, rmvp);
rmvp.setPercentage(Double.parseDouble(percentage));
rmvp.setInputFormat(dataSet);
Instances testDataSet = Filter.useFilter(dataSet, rmvp);

public void testInverting() {
 // non-inverted
 m_Filter = getFilter();
 ((RemovePercentage) m_Filter).setPercentage(20.0);
 Instances result = useFilter();
 // inverted
 m_Filter = getFilter();
 ((RemovePercentage) m_Filter).setPercentage(20.0);
 ((RemovePercentage) m_Filter).setInvertSelection(true);
 Instances resultInv = useFilter();
 assertEquals(
   m_Instances.numInstances(), 
   result.numInstances() + resultInv.numInstances());
}

@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);
  }
}

public void testInverting() {
 // non-inverted
 m_Filter = getFilter();
 ((RemovePercentage) m_Filter).setPercentage(20.0);
 Instances result = useFilter();
 // inverted
 m_Filter = getFilter();
 ((RemovePercentage) m_Filter).setPercentage(20.0);
 ((RemovePercentage) m_Filter).setInvertSelection(true);
 Instances resultInv = useFilter();
 assertEquals(
   m_Instances.numInstances(), 
   result.numInstances() + resultInv.numInstances());
}

RemovePercentage rmvp = new RemovePercentage();
rmvp.setInvertSelection(true);
rmvp.setPercentage(samplingPercentage);
rmvp.setInputFormat(dataSet);
sampledDataSet = Filter.useFilter(dataSet, rmvp);

/**
 * 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};
}

rp.setPercentage(98);
rp.setInputFormat(data);
data = Filter.useFilter(data, rp);

dataSubSet.randomize(m_random);
RemovePercentage rp = new RemovePercentage();
rp.setPercentage( m_RemovedPercentage );
rp.setInputFormat( dataSubSet );
dataSubSet = Filter.useFilter( dataSubSet, rp );

RemovePercentage rp = new RemovePercentage();
rp.setInputFormat(rel);
rp.setPercentage(rand.nextDouble()*100);
final Instances rel2 = Filter.useFilter(rel, rp);
final int i = generated.attribute(0).addRelation(rel2);

rp.setPercentage(95);
rp.setInputFormat(data);
data = Filter.useFilter(data, rp);

RemovePercentage rp = new RemovePercentage();
rp.setInputFormat(data);
rp.setPercentage(98);
final Instances dataFiltered = Filter.useFilter(data, rp);