OPTICSList (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- elki.clustering.optics.AbstractOPTICS<O>
- - elki.clustering.optics.OPTICSList<O>

Type Parameters:

O - the type of objects handled by the algorithm

All Implemented Interfaces:

elki.Algorithm, OPTICSTypeAlgorithm
```
@Title("OPTICS: Density-Based Hierarchical Clustering (implementation using a list)")
@Reference(authors="Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, J\u00f6rg Sander",
           title="OPTICS: Ordering Points to Identify the Clustering Structure",
           booktitle="Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD \'99)",
           url="https://doi.org/10.1145/304181.304187",
           bibkey="DBLP:conf/sigmod/AnkerstBKS99")
public class OPTICSList<O>
extends AbstractOPTICS<O>
```
The OPTICS algorithm for density-based hierarchical clustering.
Algorithm to find density-connected sets in a database based on the parameters 'minPts' and 'epsilon' (specifying a volume). These two parameters determine a density threshold for clustering.
This version is implemented using a list, always scanning the list for the maximum. While this could be cheaper than the complex heap updates, benchmarks indicate the heap version is usually still preferable.
Reference:
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander
OPTICS: Ordering Points to Identify the Clustering Structure
Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD '99)

Since:

0.7.0

Author:

Elke Achtert, Erich Schubert

- Nested Class Summary
  
  Nested Classes
  Modifier and Type Class Description
  
  private class OPTICSList.Instance
  Instance for processing a single data set.
  
  static class OPTICSList.Par<O>
  Parameterization class.
  - Nested classes/interfaces inherited from interface elki.Algorithm
    elki.Algorithm.Utils
- Field Summary
  
  Fields
  Modifier and Type Field Description
  
  private static elki.logging.Logging LOG
  The logger for this class.
  - Fields inherited from class elki.clustering.optics.AbstractOPTICS
    distance, epsilon, minpts
- Constructor Summary
  
  Constructors
  Constructor Description
  
  OPTICSList(elki.distance.Distance<? super O> distance, double epsilon, int minpts)
  Constructor.
- Method Summary
  
  All Methods Instance Methods Concrete Methods
  Modifier and Type Method Description
  
  ClusterOrder run(elki.database.relation.Relation<O> relation)
  Run OPTICS on the database.
  - Methods inherited from class elki.clustering.optics.AbstractOPTICS
    getInputTypeRestriction, getMinPts
  - Methods inherited from class java.lang.Object
    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
  - Methods inherited from interface elki.clustering.optics.OPTICSTypeAlgorithm
    autorun

- Field Detail
  - LOG
```
private static final elki.logging.Logging LOG
```
    The logger for this class.
- Constructor Detail
  - OPTICSList
```
public OPTICSList(elki.distance.Distance<? super O> distance,
                  double epsilon,
                  int minpts)
```
    Constructor.
    
    Parameters:
    
    distance - Distance function
    
    epsilon - Epsilon value
    
    minpts - Minpts value
- Method Detail
  - run
```
public ClusterOrder run(elki.database.relation.Relation<O> relation)
```
    Description copied from class: AbstractOPTICS
    
    Run OPTICS on the database.
    
    Specified by:
    
    run in class AbstractOPTICS<O>
    
    Parameters:
    
    relation - Relation
    
    Returns:
    
    Result