List of instance() Examples

Examples of instance()

com.complexible.common.openrdf.util.GraphBuilder.instance()
com.facebook.presto.jdbc.internal.jackson.databind.ser.impl.ReadOnlyClassToSerializerMap.instance()
com.fasterxml.jackson.databind.ser.impl.ReadOnlyClassToSerializerMap.instance()
com.foundationdb.server.types.TClass.instance()
kodkod.engine.Solution.instance()
Returns a satisfiying instance for this.formula, if the value returned by {@link #outcome() this.outcome()} is eitherSATISFIABLE or TRIVIALLY_SATISFIABLE. Otherwise returns null. @return a satisfying instance for this.formula, if one exists.
net.kuujo.copycat.test.TestNode.instance()
Returns the node context.
org.codehaus.jackson.map.ser.impl.ReadOnlyClassToSerializerMap.instance()
org.gatein.pc.portlet.impl.jsr168.PortletFilterImpl.instance()
org.jboss.weld.environment.se.WeldContainer.instance()
Provides access to all beans within the application. For example: Foo foo = weld.instance().select(Foo.class).get();
org.jboss.weld.manager.BeanManagerImpl.instance()
weka.core.Instances.instance()
Returns the instance at the given position. @param index the instance's index (index starts with 0) @return the instance at the given position

Examples of weka.core.Instances.instance()


    // set all targets to missing
    List<String> fieldsToForecast = AbstractForecaster.stringToList(forecaster
        .getFieldsToForecast());
    for (int i = 0; i < overlay.numInstances(); i++) {
      Instance current = overlay.instance(i);
      for (String target : fieldsToForecast) {
        current.setValue(overlay.attribute(target), Utils.missingValue());
      }
    }

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Examples of weka.core.Instances.instance()

      /*
       * // don't push the first instance into the filters because this one //
       * has already been pushed in earlier.
       */
      for (int i = 0; i < missingReplaced.numInstances(); i++) {
        applyFilters(missingReplaced.instance(i), false, false);
      }
      m_missingBuffer = new Instances(m_primedInput, 0);
      // m_previousPrimeInstance = inst;
    } else if (!wasBuffered) {
      applyFilters(inst, false, false);

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Examples of weka.core.Instances.instance()

          .replaceMissing(m_missingBuffer, m_fieldsToForecast,
              m_lagMaker.getTimeStampField(), false,
              m_lagMaker.getPeriodicity(), m_lagMaker.getSkipEntries());


      for (int i = 0; i < m_missingBuffer.numInstances(); i++) {
        applyFilters(missingReplaced.instance(i), false, false);
      }


      for (PrintStream p : progress) {
        p.println("WARNING: priming data contained missing target/date values that could "
            + "not be interpolated/replaced. Forecasting performance may be "

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Examples of weka.core.Instances.instance()


    m_forecastingStatus = Status.BUSY;
    processInstance(null, true);


    for (int i = 0; i < data.numInstances(); i++) {
      processInstance(data.instance(i), false);
    }


    processInstance(null, false); // finished


    // generate forecast

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Examples of weka.core.Instances.instance()

       * weighted average over all one-vs-all binary classification problems
       * that can be derived from the multiclass problem, where weights
       * correspond to class prior probabilities. */
      double[] classProps = new double[data.numClasses()];
      for ( int i = 0; i < data.numInstances(); i++ )
        classProps[ (int) data.instance(i).classValue() ] += data.instance(i).weight();
      Utils.normalize(classProps);


      double[][] aucScore = new double[classifiers.length][numRuns];
      double[][] accyScore = new double[classifiers.length][numRuns];
      double[][] timeScore = new double[classifiers.length][numRuns];

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Examples of weka.core.Instances.instance()

       * weighted average over all one-vs-all binary classification problems
       * that can be derived from the multiclass problem, where weights
       * correspond to class prior probabilities. */
      double[] classProps = new double[data.numClasses()];
      for ( int i = 0; i < data.numInstances(); i++ )
        classProps[ (int) data.instance(i).classValue() ] += data.instance(i).weight();
      Utils.normalize(classProps);


      double[][] aucScore = new double[classifiers.length][numRuns];
      double[][] accyScore = new double[classifiers.length][numRuns];
      double[][] timeScore = new double[classifiers.length][numRuns];

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Examples of weka.core.Instances.instance()

          if(!m_DataBaseConnection.isConnected())
              connectToDatabase();
          setWriteMode(WRITE);
          writeStructure();
          for(int i = 0; i < instances.numInstances(); i++){
            writeInstance(instances.instance(i));
          }
          m_DataBaseConnection.disconnectFromDatabase();
          setWriteMode(WAIT);
          resetStructure();
          m_count = 1;

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Examples of weka.core.Instances.instance()

      }
      String[] options = weka.core.Utils.splitOptions("-p 0");
      J48 cls = (J48)weka.core.SerializationHelper.read(modelfile);
      cls.setOptions(options);
      for(int i = 0; i < data.numInstances(); i++){
        double pred = cls.classifyInstance(data.instance(i));
        ClusterClass clusClass = ClusterClass.valueOf(
            data.classAttribute().value((int)pred).toUpperCase());
        if(!retval.containsKey(clusClass)){
          retval.put(clusClass, new ArrayList<StoredDomainCluster>());
        }

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Examples of weka.core.Instances.instance()

    Attribute groupID = new Attribute("groupID", (FastVector) null);
    
    DataSource source = new DataSource("testMe.arff");
    Instances instances = source.getDataSet();
    //System.out.println(instances);
    System.out.println(instances.instance(0));
    
        
    Enumeration enu = instances.enumerateInstances();
    while(enu.hasMoreElements())
    {

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