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HDBSCANHierarchyExtraction$TempCluster.totalStability
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totalStability
method
in
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction$TempCluster

Best Java code snippets using de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction$TempCluster.totalStability (Showing top 6 results out of 315)

origin: de.lmu.ifi.dbs.elki/elki-clustering

/**
 * Excess of mass measure.
 *
 * @return Excess of mass
 */
public double totalStability() {
 double stability = excessOfMass();
 double cstab = 0.;
 for(TempCluster child : children) {
  cstab += Math.abs(child.totalStability());
 }
 return stability > cstab ? stability : -cstab;
}
origin: elki-project/elki

/**
 * Excess of mass measure.
 *
 * @return Excess of mass
 */
public double totalStability() {
 double stability = excessOfMass();
 double cstab = 0.;
 for(TempCluster child : children) {
  cstab += Math.abs(child.totalStability());
 }
 return stability > cstab ? stability : -cstab;
}
origin: de.lmu.ifi.dbs.elki/elki

/**
 * Excess of mass measure.
 *
 * @return Excess of mass
 */
public double totalStability() {
 double stability = excessOfMass();
 double cstab = 0.;
 for(TempCluster child : children) {
  cstab += Math.abs(child.totalStability());
 }
 return stability > cstab ? stability : -cstab;
}
origin: de.lmu.ifi.dbs.elki/elki

 /**
  * Recursive flattening of clusters.
  *
  * @param clustering Output clustering
  * @param cur Current temporary cluster
  * @param clus Output cluster
  * @param flatten Flag to indicate everything below should be flattened.
  * @param hierarchical Hierarchical output
  */
 private void collectChildren(Clustering<DendrogramModel> clustering, TempCluster cur, Cluster<DendrogramModel> clus, boolean flatten, boolean hierarchical) {
  for(TempCluster child : cur.children) {
   if(flatten || child.totalStability() < 0) {
    members.addDBIDs(child.members);
    collectChildren(clustering, child, clus, flatten, hierarchical);
   }
   else {
    child.finalizeCluster(clustering, clus, true, hierarchical);
   }
  }
 }
}
origin: de.lmu.ifi.dbs.elki/elki-clustering

 /**
  * Recursive flattening of clusters.
  *
  * @param clustering Output clustering
  * @param cur Current temporary cluster
  * @param clus Output cluster
  * @param flatten Flag to indicate everything below should be flattened.
  */
 private void collectChildren(TempCluster temp, Clustering<DendrogramModel> clustering, TempCluster cur, Cluster<DendrogramModel> clus, boolean flatten) {
  for(TempCluster child : cur.children) {
   if(flatten || child.totalStability() < 0) {
    temp.members.addDBIDs(child.members);
    collectChildren(temp, clustering, child, clus, flatten);
   }
   else {
    finalizeCluster(child, clustering, clus, true);
   }
  }
 }
}
origin: elki-project/elki

 /**
  * Recursive flattening of clusters.
  *
  * @param clustering Output clustering
  * @param cur Current temporary cluster
  * @param clus Output cluster
  * @param flatten Flag to indicate everything below should be flattened.
  */
 private void collectChildren(TempCluster temp, Clustering<DendrogramModel> clustering, TempCluster cur, Cluster<DendrogramModel> clus, boolean flatten) {
  for(TempCluster child : cur.children) {
   if(flatten || child.totalStability() < 0) {
    temp.members.addDBIDs(child.members);
    collectChildren(temp, clustering, child, clus, flatten);
   }
   else {
    finalizeCluster(child, clustering, clus, true);
   }
  }
 }
}
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extractionHDBSCANHierarchyExtraction$TempClustertotalStability

Javadoc

Excess of mass measure.

Popular methods of HDBSCANHierarchyExtraction$TempCluster

  • <init>
    Constructor.
  • excessOfMass
    Excess of mass measure.
  • grow
    Add new objects to the cluster.
  • isSpurious
    Test if a cluster is spurious.
  • resetAggregate
    Reset the aggregate (for spurious clusters).
  • totalElements
    Total number of elements in this subtree.
  • collectChildren
    Recursive flattening of clusters.
  • finalizeCluster
    Make the cluster for the given object

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