Examples of weka.core.Instances.deleteWithMissingClass()

weka.core.Instances.deleteWithMissingClass()
Removes all instances with a missing class value from the dataset. @throws UnassignedClassException if class is not set

        if (data.classAttribute().type() != Attribute.NOMINAL) {
            throw new Exception("Class attribute must be nominal");
        }
        int numClasses = data.numClasses();


        data.deleteWithMissingClass();
        if ( data.checkForStringAttributes() ) {
            throw new Exception("Can't handle string attributes!");
        }


        // Dataset size must be greater than 2

View Full Code Here

    // can classifier handle the data?
    getCapabilities().testWithFail(data);


    // remove instances with missing class
    Instances newData = new Instances(data);
    newData.deleteWithMissingClass();


    double sum = 0;
    double temp_sum = 0;
    // Add the model for the mean first
    m_zeroR = new ZeroR();

View Full Code Here

    if (data.classAttribute().type() != Attribute.NOMINAL) {
      throw new Exception("Class attribute must be nominal");
    }
    int numClasses = data.numClasses();


    data.deleteWithMissingClass();
    if (data.checkForStringAttributes()) {
      throw new Exception("Can't handle string attributes!");
    }


    if (data.numInstances() < 2 * m_TrainPoolSize) {

View Full Code Here

    // can classifier handle the data?
    getCapabilities().testWithFail(instances);


    // remove instances with missing class
    Instances data = new Instances(instances);
    data.deleteWithMissingClass();


    // only class? -> build ZeroR model
    if (data.numAttributes() == 1) {
      System.err.println(
    "Cannot build model (only class attribute present in data!), "

View Full Code Here

   */
  public void buildClassifier(Instances data) throws Exception {


    // remove instances with missing class
    Instances newData = new Instances(data);
    newData.deleteWithMissingClass();


    m_Random = new Random(getSeed());
    
    m_preBuiltClassifiers.clear();
    if (m_classifiersToLoad.size() > 0) {

View Full Code Here

    getCapabilities().testWithFail(data);


    // remove instances with missing class
    Instances newData = new Instances(data);
    m_BaseFormat = new Instances(data, 0);
    newData.deleteWithMissingClass();
    
    Random random = new Random(m_Seed);
    newData.randomize(random);
    if (newData.classAttribute().isNominal()) {
      newData.stratify(m_NumFolds);

View Full Code Here

    // can classifier handle the data?
    getCapabilities().testWithFail(data);


    // remove instances with missing class
    Instances newData = new Instances(data);
    newData.deleteWithMissingClass();
    
    Random random = new Random(m_Seed);
    newData.randomize(random);
    if (newData.classAttribute().isNominal() && (m_NumXValFolds > 1)) {
      newData.stratify(m_NumXValFolds);

View Full Code Here

    // can classifier handle the data?
    getCapabilities().testWithFail(data);


    // remove instances with missing class
    Instances filteredData = new Instances(data);
    filteredData.deleteWithMissingClass();
    
    //replace missing values
    m_replaceMissing = new ReplaceMissingValues();
    m_replaceMissing.setInputFormat(filteredData);  
    filteredData = Filter.useFilter(filteredData, m_replaceMissing);

View Full Code Here

0 1 2 3 4

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.