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RemovePercentage.<init>
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How to use
weka.filters.unsupervised.instance.RemovePercentage
constructor

Best Java code snippets using weka.filters.unsupervised.instance.RemovePercentage.<init> (Showing top 14 results out of 315)

origin: nz.ac.waikato.cms.weka/weka-stable

/** Creates a default RemovePercentage */
public Filter getFilter() {
 RemovePercentage f = new RemovePercentage();
 return f;
}
origin: Waikato/weka-trunk

 /**
  * 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);
 }
}
origin: nz.ac.waikato.cms.weka/weka-stable

 /**
  * 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);
 }
}
origin: Waikato/weka-trunk

/** Creates a default RemovePercentage */
public Filter getFilter() {
 RemovePercentage f = new RemovePercentage();
 return f;
}
origin: Waikato/wekaDeeplearning4j

/**
 * 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};
}
origin: net.sf.meka.thirdparty/mulan

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);
origin: net.sf.meka.thirdparty/mulan

@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);
  }
}
origin: net.sf.meka.thirdparty/mulan

RemovePercentage rmvp = new RemovePercentage();
rmvp.setInvertSelection(true);
rmvp.setPercentage(samplingPercentage);
origin: Waikato/wekaDeeplearning4j

/**
 * 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};
}
origin: Waikato/wekaDeeplearning4j

RemovePercentage rp = new RemovePercentage();
rp.setPercentage(98);
rp.setInputFormat(data);
origin: nz.ac.waikato.cms.weka/rotationForest

RemovePercentage rp = new RemovePercentage();
rp.setPercentage( m_RemovedPercentage );
rp.setInputFormat( dataSubSet );
origin: Waikato/wekaDeeplearning4j

for (Instance datum : generated) {
 final Instances rel = datum.relationalValue(0);
 RemovePercentage rp = new RemovePercentage();
 rp.setInputFormat(rel);
 rp.setPercentage(rand.nextDouble()*100);
origin: Waikato/wekaDeeplearning4j

RemovePercentage rp = new RemovePercentage();
rp.setPercentage(95);
rp.setInputFormat(data);
origin: Waikato/wekaDeeplearning4j

RemovePercentage rp = new RemovePercentage();
rp.setInputFormat(data);
rp.setPercentage(98);
weka.filters.unsupervised.instanceRemovePercentage<init>

Popular methods of RemovePercentage

  • setPercentage
    Sets the percentage of intances to select.
  • setInvertSelection
    Sets if selection is to be inverted.
  • setInputFormat
    Sets the format of the input instances.
  • bufferInput
  • flushInput
  • getInputFormat
  • getInvertSelection
    Gets if selection is to be inverted.
  • getPercentage
    Gets the percentage of instances to select.
  • isFirstBatchDone
  • numPendingOutput
  • push
  • resetQueue
  • push,
  • resetQueue,
  • runFilter,
  • setOutputFormat

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