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java.lang.Object de.lmu.ifi.dbs.elki.logging.AbstractLoggable de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<O> de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm<O,D> de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN<O,D>
O
- the type of DatabaseObject the algorithm is applied onD
- the type of Distance usedpublic class DBSCAN<O extends DatabaseObject,D extends Distance<D>>
DBSCAN provides the DBSCAN algorithm, an algorithm to find density-connected sets in a database.
Reference:
M. Ester, H.-P. Kriegel, J. Sander, and X. Xu:
A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.
In Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD '96), Portland, OR, 1996.
Field Summary | |
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private String |
epsilon
Holds the value of EPSILON_PARAM . |
static OptionID |
EPSILON_ID
OptionID for EPSILON_PARAM |
private PatternParameter |
EPSILON_PARAM
Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified. |
protected int |
minpts
Holds the value of MINPTS_PARAM . |
static OptionID |
MINPTS_ID
OptionID for MINPTS_PARAM |
private IntParameter |
MINPTS_PARAM
Parameter to specify the threshold for minimum number of points in the epsilon-neighborhood of a point, must be an integer greater than 0. |
protected Set<Integer> |
noise
Holds a set of noise. |
protected Set<Integer> |
processedIDs
Holds a set of processed ids. |
protected ClustersPlusNoise<O> |
result
Provides the result of the algorithm. |
protected List<List<Integer>> |
resultList
Holds a list of clusters found. |
Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm |
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DISTANCE_FUNCTION_ID, DISTANCE_FUNCTION_PARAM |
Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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optionHandler |
Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debug |
Constructor Summary | |
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DBSCAN()
Provides the DBSCAN algorithm, adding parameters EPSILON_PARAM and
MINPTS_PARAM to the option handler
additionally to parameters of super class. |
Method Summary | |
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protected void |
expandCluster(Database<O> database,
Integer startObjectID,
Progress progress)
DBSCAN-function expandCluster. |
Description |
getDescription()
Returns a description of the algorithm. |
ClustersPlusNoise<O> |
getResult()
Returns the result of the algorithm. |
protected void |
runInTime(Database<O> database)
Performs the DBSCAN algorithm on the given database. |
String[] |
setParameters(String[] args)
Calls DistanceBasedAlgorithm#setParameters(args)
and sets additionally the values of the parameters
EPSILON_PARAM and MINPTS_PARAM . |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm |
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getAttributeSettings, getDistanceFunction |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm |
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description, isTime, isVerbose, run, setTime, setVerbose |
Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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addOption, checkGlobalParameterConstraints, deleteOption, description, description, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters |
Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debugFine, debugFiner, debugFinest, exception, message, progress, progress, progress, verbose, verbose, warning |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.Algorithm |
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run, setTime, setVerbose |
Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable |
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checkGlobalParameterConstraints, description, getAttributeSettings, getParameters, getPossibleOptions, inlineDescription |
Field Detail |
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public static final OptionID EPSILON_ID
EPSILON_PARAM
private final PatternParameter EPSILON_PARAM
Key: -dbscan.epsilon
private String epsilon
EPSILON_PARAM
.
public static final OptionID MINPTS_ID
MINPTS_PARAM
private final IntParameter MINPTS_PARAM
Key: -dbscan.minpts
protected int minpts
MINPTS_PARAM
.
protected List<List<Integer>> resultList
protected ClustersPlusNoise<O extends DatabaseObject> result
protected Set<Integer> noise
protected Set<Integer> processedIDs
Constructor Detail |
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public DBSCAN()
EPSILON_PARAM
and
MINPTS_PARAM
to the option handler
additionally to parameters of super class.
Method Detail |
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protected void runInTime(Database<O> database) throws IllegalStateException
runInTime
in class AbstractAlgorithm<O extends DatabaseObject>
database
- the database to run the algorithm on
IllegalStateException
- if the algorithm has not been initialized
properly (e.g. the setParameters(String[]) method has been failed
to be called).AbstractAlgorithm.runInTime(de.lmu.ifi.dbs.elki.database.Database)
protected void expandCluster(Database<O> database, Integer startObjectID, Progress progress)
database
- the database on which the algorithm is runstartObjectID
- potential seed of a new potential clusterprogress
- the progress object for logging the current statuspublic Description getDescription()
Algorithm
getDescription
in interface Algorithm<O extends DatabaseObject>
Algorithm.getDescription()
public String[] setParameters(String[] args) throws ParameterException
DistanceBasedAlgorithm#setParameters(args)
and sets additionally the values of the parameters
EPSILON_PARAM
and MINPTS_PARAM
.
setParameters
in interface Parameterizable
setParameters
in class DistanceBasedAlgorithm<O extends DatabaseObject,D extends Distance<D>>
args
- parameters to set the attributes accordingly to
ParameterException
- in case of wrong parameter-settingParameterizable.setParameters(String[])
public ClustersPlusNoise<O> getResult()
Algorithm
getResult
in interface Algorithm<O extends DatabaseObject>
getResult
in interface Clustering<O extends DatabaseObject>
Algorithm.getResult()
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