| Package | Description |
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.clustering |
Clustering algorithms.
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
| de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
| de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments |
Pair-segment analysis of multiple clusterings.
|
| de.lmu.ifi.dbs.elki.evaluation.roc |
Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
|
| de.lmu.ifi.dbs.elki.result.textwriter |
Text serialization (CSV, Gnuplot, Console, ...)
|
| de.lmu.ifi.dbs.elki.result.textwriter.naming |
Naming schemes for clusters (for output when an algorithm doesn't generate cluster names).
|
| de.lmu.ifi.dbs.elki.visualization.visualizers.optics |
Visualizers that do work on OPTICS plots
|
| Modifier and Type | Method and Description |
|---|---|
private Cluster<DendrogramModel<D>> |
SLINK.makeCluster(DBIDRef lead,
D depth,
DBIDs members,
ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
Make the cluster for the given object
|
| Modifier and Type | Method and Description |
|---|---|
private Cluster<DendrogramModel<D>> |
SLINK.makeCluster(DBIDRef lead,
D depth,
DBIDs members,
ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
Make the cluster for the given object
|
| Modifier and Type | Method and Description |
|---|---|
private SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> |
ERiC.extractCorrelationClusters(Clustering<Model> copacResult,
Relation<V> database,
int dimensionality)
Extracts the correlation clusters and noise from the copac result and
returns a mapping of correlation dimension to maps of clusters within this
correlation dimension.
|
| Modifier and Type | Method and Description |
|---|---|
private boolean |
ERiC.isParent(ERiCDistanceFunction distanceFunction,
Cluster<CorrelationModel<V>> parent,
List<Cluster<CorrelationModel<V>>> children)
Returns true, if the specified parent cluster is a parent of one child of
the children clusters.
|
| Modifier and Type | Method and Description |
|---|---|
private void |
ERiC.buildHierarchy(SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> clusterMap,
DistanceQuery<V,IntegerDistance> query) |
private boolean |
ERiC.isParent(ERiCDistanceFunction distanceFunction,
Cluster<CorrelationModel<V>> parent,
List<Cluster<CorrelationModel<V>>> children)
Returns true, if the specified parent cluster is a parent of one child of
the children clusters.
|
| Modifier and Type | Method and Description |
|---|---|
private List<Cluster<Model>> |
SUBCLU.runDBSCAN(Relation<V> relation,
DBIDs ids,
Subspace subspace)
Runs the DBSCAN algorithm on the specified partition of the database in the
given subspace.
|
private List<Cluster<SubspaceModel<V>>> |
DiSH.sortClusters(Relation<V> database,
Map<BitSet,List<Pair<BitSet,ArrayModifiableDBIDs>>> clustersMap)
Returns a sorted list of the clusters w.r.t. the subspace dimensionality in
descending order.
|
| Modifier and Type | Method and Description |
|---|---|
private boolean |
DiSH.isParent(Relation<V> database,
DiSHDistanceFunction.Instance<V> distFunc,
Cluster<SubspaceModel<V>> parent,
List<Cluster<SubspaceModel<V>>> children)
Returns true, if the specified parent cluster is a parent of one child of
the children clusters.
|
| Modifier and Type | Method and Description |
|---|---|
private Subspace |
SUBCLU.bestSubspace(List<Subspace> subspaces,
Subspace candidate,
TreeMap<Subspace,List<Cluster<Model>>> clusterMap)
Determines the
d-dimensional subspace of the (d+1)
-dimensional candidate with minimal number of objects in the cluster. |
private void |
DiSH.buildHierarchy(Relation<V> database,
DiSHDistanceFunction.Instance<V> distFunc,
List<Cluster<SubspaceModel<V>>> clusters,
int dimensionality)
Builds the cluster hierarchy.
|
private boolean |
DiSH.isParent(Relation<V> database,
DiSHDistanceFunction.Instance<V> distFunc,
Cluster<SubspaceModel<V>> parent,
List<Cluster<SubspaceModel<V>>> children)
Returns true, if the specified parent cluster is a parent of one child of
the children clusters.
|
| Modifier and Type | Field and Description |
|---|---|
private Hierarchy<Cluster<M>> |
Cluster.hierarchy
Object that the hierarchy management is delegated to.
|
private List<Cluster<M>> |
Clustering.toplevelclusters
Keep a list of top level clusters.
|
| Modifier and Type | Method and Description |
|---|---|
List<Cluster<M>> |
Clustering.getAllClusters()
Collect all clusters (recursively) into a List.
|
List<Cluster<M>> |
Cluster.getChildren()
Delegate to hierarchy object
|
Set<Cluster<M>> |
Cluster.getDescendants()
Collect descendants
|
Hierarchy<Cluster<M>> |
Cluster.getHierarchy()
Get hierarchy object
|
List<Cluster<M>> |
Cluster.getParents()
Delegate to hierarchy object
|
List<Cluster<M>> |
Clustering.getToplevelClusters()
Return top level clusters
|
Iterator<Cluster<M>> |
Cluster.iterAncestors()
Delegate to hierarchy object
|
Iterator<Cluster<M>> |
Cluster.iterDescendants()
Delegate to hierarchy object
|
| Modifier and Type | Method and Description |
|---|---|
void |
Clustering.addCluster(Cluster<M> n)
Add a cluster to the clustering.
|
int |
Cluster.PartialComparator.compare(Cluster<?> o1,
Cluster<?> o2) |
int |
Cluster.PartialComparator.compare(Cluster<?> o1,
Cluster<?> o2) |
| Modifier and Type | Method and Description |
|---|---|
void |
Cluster.setHierarchy(Hierarchy<Cluster<M>> hierarchy)
Set hierarchy object
|
| Constructor and Description |
|---|
Cluster(String name,
DBIDs ids,
boolean noise,
M model,
Hierarchy<Cluster<M>> hierarchy)
Full constructor
|
Cluster(String name,
DBIDs ids,
boolean noise,
M model,
List<Cluster<M>> children,
List<Cluster<M>> parents)
Constructor with hierarchy information.
|
Cluster(String name,
DBIDs ids,
boolean noise,
M model,
List<Cluster<M>> children,
List<Cluster<M>> parents)
Constructor with hierarchy information.
|
Cluster(String name,
DBIDs ids,
M model,
Hierarchy<Cluster<M>> hierarchy)
Constructor with hierarchy but noise flag defaulting to false.
|
Cluster(String name,
DBIDs ids,
M model,
List<Cluster<M>> children,
List<Cluster<M>> parents)
Constructor with hierarchy information, but no noise flag.
|
Cluster(String name,
DBIDs ids,
M model,
List<Cluster<M>> children,
List<Cluster<M>> parents)
Constructor with hierarchy information, but no noise flag.
|
Clustering(String name,
String shortname,
List<Cluster<M>> toplevelclusters)
Constructor with a list of top level clusters
|
| Modifier and Type | Field and Description |
|---|---|
private List<List<? extends Cluster<?>>> |
Segments.clusters
Clusters
|
| Modifier and Type | Method and Description |
|---|---|
private void |
Segments.recursivelyFill(List<List<? extends Cluster<?>>> cs) |
private void |
Segments.recursivelyFill(List<List<? extends Cluster<?>>> cs,
int depth,
SetDBIDs first,
SetDBIDs second,
int[] path,
boolean objectsegment) |
| Modifier and Type | Method and Description |
|---|---|
static <D extends Distance<D>> |
ROC.computeROCAUCDistanceResult(int size,
Cluster<?> clus,
DistanceDBIDResult<D> nei)
Compute a ROC curves Area-under-curve for a QueryResult and a Cluster.
|
| Modifier and Type | Method and Description |
|---|---|
private void |
TextWriter.writeClusterResult(Database db,
StreamFactory streamOpener,
Cluster<?> clus,
List<Relation<?>> ra,
NamingScheme naming,
List<SettingsResult> sr) |
| Modifier and Type | Field and Description |
|---|---|
private Map<Cluster<?>,String> |
SimpleEnumeratingScheme.names
Assigned cluster names.
|
| Modifier and Type | Method and Description |
|---|---|
String |
SimpleEnumeratingScheme.getNameFor(Cluster<?> cluster)
Retrieve the cluster name.
|
String |
NamingScheme.getNameFor(Cluster<?> cluster)
Retrieve a name for the given cluster.
|
| Modifier and Type | Method and Description |
|---|---|
private void |
OPTICSClusterVisualization.Instance.drawClusters(List<Cluster<OPTICSModel>> clusters,
int depth,
Map<Cluster<?>,String> colormap)
Recursively draw clusters
|
private void |
OPTICSClusterVisualization.Instance.drawClusters(List<Cluster<OPTICSModel>> clusters,
int depth,
Map<Cluster<?>,String> colormap)
Recursively draw clusters
|