de.lmu.ifi.dbs.elki.algorithm.clustering.trivial

Class ByLabelClustering

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<Clustering<Model>>

de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<Model>>, InspectionUtilFrequentlyScanned, Parameterizable

Direct Known Subclasses:

ByLabelOrAllInOneClustering

@Title(value="Clustering by label")
@Description(value="Cluster points by a (pre-assigned!) label. For comparing results with a reference clustering.")
public class ByLabelClustering
extends AbstractAlgorithm<Clustering<Model>>
implements ClusteringAlgorithm<Clustering<Model>>

Pseudo clustering using labels. This "algorithm" puts elements into the same cluster when they agree in their labels. I.e. it just uses a predefined clustering, and is mostly useful for testing and evaluation (e.g. comparing the result of a real algorithm to a reference result / golden standard). If an assignment of an object to multiple clusters is desired, the labels of the object indicating the clusters need to be separated by blanks and the flag MULTIPLE_ID needs to be set. TODO: handling of data sets with no labels?

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ByLabelClustering.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	logger The logger for this class.
private boolean	multiple Holds the value of MULTIPLE_ID.
static OptionID	MULTIPLE_ID Flag to indicate that multiple cluster assignment is possible.
static OptionID	NOISE_ID Pattern to recognize noise clusters by.
private Pattern	noisepattern Holds the value of NOISE_ID.

Constructor Summary

Constructors

Constructor and Description
ByLabelClustering() Constructor without parameters
ByLabelClustering(boolean multiple, Pattern noisepattern) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
private void	assign(HashMap<String,DBIDs> labelMap, String label, DBIDRef id) Assigns the specified id to the labelMap according to its label
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
private HashMap<String,DBIDs>	multipleAssignment(Relation<?> data) Assigns the objects of the database to multiple clusters according to their labels.
Clustering<Model>	run(Database database) Runs the algorithm.
Clustering<Model>	run(Relation<?> relation) Run the actual clustering algorithm.
private HashMap<String,DBIDs>	singleAssignment(Relation<?> data) Assigns the objects of the database to single clusters according to their labels.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

makeParameterDistanceFunction

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

logger

private static final Logging logger

The logger for this class.

MULTIPLE_ID

public static final OptionID MULTIPLE_ID

Flag to indicate that multiple cluster assignment is possible. If an assignment to multiple clusters is desired, the labels indicating the clusters need to be separated by blanks.

NOISE_ID

public static final OptionID NOISE_ID

Pattern to recognize noise clusters by.

multiple

private boolean multiple

Holds the value of MULTIPLE_ID.

noisepattern

private Pattern noisepattern

Holds the value of NOISE_ID.

Constructor Detail

ByLabelClustering

public ByLabelClustering(boolean multiple,
                 Pattern noisepattern)

Constructor.

Parameters:

multiple - Allow multiple cluster assignments

noisepattern - Noise pattern

ByLabelClustering

public ByLabelClustering()

Constructor without parameters

Method Detail

run

public Clustering<Model> run(Database database)

Description copied from interface: Algorithm

Runs the algorithm.

Specified by:

run in interface Algorithm

Specified by:

run in interface ClusteringAlgorithm<Clustering<Model>>

Overrides:

run in class AbstractAlgorithm<Clustering<Model>>

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm

run

public Clustering<Model> run(Relation<?> relation)

Run the actual clustering algorithm.

Parameters:

relation - The data input we use

singleAssignment

private HashMap<String,DBIDs> singleAssignment(Relation<?> data)

Assigns the objects of the database to single clusters according to their labels.

Parameters:

data - the database storing the objects

Returns:

a mapping of labels to ids

multipleAssignment

private HashMap<String,DBIDs> multipleAssignment(Relation<?> data)

Assigns the objects of the database to multiple clusters according to their labels.

Parameters:

data - the database storing the objects

Returns:

a mapping of labels to ids

assign

private void assign(HashMap<String,DBIDs> labelMap,
          String label,
          DBIDRef id)

Assigns the specified id to the labelMap according to its label

Parameters:

labelMap - the mapping of label to ids

label - the label of the object to be assigned

id - the id of the object to be assigned

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<Clustering<Model>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<Clustering<Model>>

Returns:

the static logger