code: package cic.cs.unb.ca.weka;
  
  import com.google.common.collect.ArrayListMultimap;
  import com.google.common.collect.Multimap;
  import org.apache.commons.math3.stat.descriptive.SummaryStatistics;
  import org.slf4j.Logger;
  import org.slf4j.LoggerFactory;
  import weka.clusterers.XMeans;
  import weka.core.Attribute;
  import weka.core.Instance;
  import weka.core.Instances;
  
  import java.util.Enumeration;
  
  /**
   * Created by yzhang29 on 02/01/18.
   */
  public class WekaXMeans {
      protected static final Logger logger = LoggerFactory.getLogger(WekaXMeans.class);
  
      private XMeans xmeans;
      private XMeans dimenReduceXMeans;
      private Instances orgDataSet;
      private Instances dataSetWithoutStr;
      private Instances dimenReduceDataSet;
      private SummaryStatistics[] summaryStatistics;
  
  
      public WekaXMeans(Instances instances) {
  
          if (instances == null) {
              throw new IllegalArgumentException("instances cannot be null");
          }
  
          xmeans = new XMeans();
  
          orgDataSet = new Instances(instances);
          //logger.info("orgDataSet summary-> {}",orgDataSet.toSummaryString());
          //logger.info("orgDataSet Num: {}", orgDataSet.numAttributes());
          dataSetWithoutStr = new Instances(instances);
          dataSetWithoutStr.deleteAttributeType(Attribute.NOMINAL);
          //logger.info("dataSetWithoutStr summary-> {}",dataSetWithoutStr.toSummaryString());
          //logger.info("dataSetWithoutStr Num: {}", dataSetWithoutStr.numAttributes());
  
          summaryStatistics = new SummaryStatistics[dataSetWithoutStr.numAttributes()];
  
          dimenReduceXMeans = new XMeans();
  
      }
  
      public void build(){
          buildRaw();
          buildDimenReduction();
      }
  
      public void buildRaw(){
  
          try {
              xmeans.setSeed(10);
              xmeans.setMaxNumClusters(6);
              xmeans.setMinNumClusters(3);
              xmeans.buildClusterer(dataSetWithoutStr);
          } catch (Exception e) {
              logger.debug(e.getMessage());
          }
      }
  
      public void buildDimenReduction() {
          try {
              dimenReduceDataSet = WekaFactory.dimReduce(dataSetWithoutStr, WekaFactory.DIMENREDUCE_TSNE);
              //dimenReduceDataSet = WekaUtils.dimReduce(dataSetWithoutStr, WekaUtils.DIMENREDUCE_WEKA_PCA);
  
              dimenReduceXMeans.setSeed(10);
              dimenReduceXMeans.setMaxNumClusters(6);
              dimenReduceXMeans.setMinNumClusters(3);
              dimenReduceXMeans.buildClusterer(dimenReduceDataSet);
          } catch (Exception e) {
              logger.debug(e.getMessage());
          }
      }
  
      public XMeans getDRXmeans() {
          return dimenReduceXMeans;
      }
  
      public Instances getDRDataset() {
          return dimenReduceDataSet;
      }
  
      public int getAttrIndex(Attribute attribute) {
          int index = -1;
  
          for(int i = 0; i< dataSetWithoutStr.numAttributes(); i++) {
              Attribute attr = dataSetWithoutStr.attribute(i);
  
              if(attr.name().equals(attribute.name())) {
                  index = i;
                  if(summaryStatistics[i]==null) {
                      summaryStatistics[i] = new SummaryStatistics();
                  }
                  break;
              }
          }
          return index;
      }
  
      public double getMean(Attribute attribute) {
          int index  = getAttrIndex(attribute);
  
          if (index < 0) {
              logger.info("not found {} in the data set!", attribute.name());
              return 0;
          }
  
          if(summaryStatistics[index]==null) {
              summaryStatistics[index] = new SummaryStatistics();
          }
          double[] values = dataSetWithoutStr.attributeToDoubleArray(index);
  
          if(summaryStatistics.length != values.length) {
              for(double value:values) {
                  summaryStatistics[index].addValue(value);
              }
          }
          return summaryStatistics[index].getMean();
      }
  
      private int getAttrIndex(Instances dataSet, Attribute attribute) {
          int index = -1;
          for(int i = 0; i< dataSet.numAttributes(); i++) {
              Attribute attr = dataSet.attribute(i);
  
              if(attr.name().equals(attribute.name())) {
                  index = i;
                  break;
              }
          }
          return index;
      }
  
      public Multimap<String, Instance> getMultiMap(Attribute attribute) {
  
          if (attribute == null) {
              throw new IllegalArgumentException("attribute should not be null!");
          }
  
          Instances instances;
          if (attribute.isNumeric()) {
              instances = dataSetWithoutStr;
          } else {
              instances = orgDataSet;
          }
  
          int index  = getAttrIndex(instances,attribute);
          if (index < 0) {
              logger.info("not found {} in the data set!", attribute.name());
              return null;
          }
          Multimap<String, Instance> attrMap = ArrayListMultimap.create();
  
          Enumeration enumInst = instances.enumerateInstances();
          while (enumInst.hasMoreElements()) {
              Instance inst = (Instance) enumInst.nextElement();
  
              String key;
              if (attribute.isNumeric()) {
                  key = String.valueOf(inst.value(index));
              } else {
                  key = inst.stringValue(index);
              }
              attrMap.put(key, inst);
          }
  
          return attrMap;
      }
  
  }
  