Package dmt.clustering

Source Code of dmt.clustering.ClusteringProcessor

package dmt.clustering;

import java.io.IOException;
import java.util.Set;
import java.util.Vector;

import com.aliasi.cluster.CompleteLinkClusterer;
import com.aliasi.cluster.Dendrogram;
import com.aliasi.cluster.HierarchicalClusterer;
import com.aliasi.cluster.SingleLinkClusterer;

import dmt.tools.CSVFileWriter;

public class ClusteringProcessor
{

  /**
   * @param args
   * @throws IOException
   */
  public static void main(String[] args) throws IOException
  {
    TextInstance.loadTextInstances();

    // eval clusterers
    HierarchicalClusterer<TextInstance> clClusterer = new CompleteLinkClusterer<TextInstance>(
        TextInstance.EUCLIDEAN_DISTANCE);
    Dendrogram<TextInstance> completeLinkDendrogram = clClusterer
        .hierarchicalCluster(TextInstance.textInstancesSet);
    int k = 30;
    Set<Set<TextInstance>> clResponsePartition = completeLinkDendrogram
        .partitionK(k);
    Object[] clusters = clResponsePartition.toArray();
    CSVFileWriter out = new CSVFileWriter("completeLinkClustersCSV.csv",
        ',');
    Vector<String> header = new Vector<String>();
    header.add("Cluster label");
    out.writeFields(header);
    Object[] textInstancesArray = TextInstance.textInstancesSet.toArray();
    for (int i = 0; i < textInstancesArray.length; i++)
    {
      for (int j = 0; j < clusters.length; j++)
      {
        if (((Set<TextInstance>) clusters[j])
            .contains(textInstancesArray[i]))
        {
          Vector<String> clusterLabel = new Vector<String>();
          clusterLabel.add((j + 1) + "");
          out.writeFields(clusterLabel);
        }
      }
    }
    out.close();

    HierarchicalClusterer<TextInstance> slClusterer = new SingleLinkClusterer<TextInstance>(
        TextInstance.EUCLIDEAN_DISTANCE);
    Dendrogram<TextInstance> singleLinkDendrogram = slClusterer
        .hierarchicalCluster(TextInstance.textInstancesSet);
    Set<Set<TextInstance>> slResponsePartition = singleLinkDendrogram
        .partitionK(k);
    clusters = slResponsePartition.toArray();
    out = new CSVFileWriter("singleLinkClustersCSV.csv", ',');
    out.writeFields(header);
    for (int i = 0; i < textInstancesArray.length; i++)
    {
      for (int j = 0; j < clusters.length; j++)
      {
        if (((Set<TextInstance>) clusters[j])
            .contains(textInstancesArray[i]))
        {
          Vector<String> clusterLabel = new Vector<String>();
          clusterLabel.add((j + 1) + "");
          out.writeFields(clusterLabel);
        }
      }
    }
    out.close();

  }
}
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