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

Class ChengAndChurch<V extends NumberVector>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering<V,BiclusterWithInversionsModel>

de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch<V>

Type Parameters:

V - Vector type.

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<BiclusterWithInversionsModel>>

@Reference(authors="Y. Cheng, G. M. Church",
           title="Biclustering of expression data",
           booktitle="Proc. 8th Int. Conf. on Intelligent Systems for Molecular Biology (ISMB)",
           url="http://www.aaai.org/Library/ISMB/2000/ismb00-010.php",
           bibkey="DBLP:conf/ismb/ChengC00")
public class ChengAndChurch<V extends NumberVector>
extends AbstractBiclustering<V,BiclusterWithInversionsModel>

Cheng and Church biclustering.

Reference:

Y. Cheng and G. M. Church.
Biclustering of expression data.
Proc. 8th Int. Conf. on Intelligent Systems for Molecular Biology (ISMB)

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
protected static class	ChengAndChurch.BiclusterCandidate Bicluster candidate.
protected static interface	ChengAndChurch.CellVisitor Visitor pattern for processing cells.
static class	ChengAndChurch.Parameterizer<V extends NumberVector> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private double	alpha The parameter for multiple node deletion.
private double	delta Threshold for the score.
private Distribution	dist Distribution to sample random replacement values from.
private static Logging	LOG The logger for this class.
private static int	MIN_COLUMN_REMOVE_THRESHOLD The minimum number of columns that the database must have so that a removal of columns is performed in multipleNodeDeletion(double[][], de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate).
private static int	MIN_ROW_REMOVE_THRESHOLD The minimum number of rows that the database must have so that a removal of rows is performed in multipleNodeDeletion(double[][], de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate).
private int	n Number of biclusters to be found.
private boolean	useinverted Allow inversion of rows in the last phase.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering

relation, rowIDs

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

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
ChengAndChurch(double delta, double alpha, int n, Distribution dist) Constructor.

Method Summary

Modifier and Type	Method and Description
Clustering<BiclusterWithInversionsModel>	biclustering() Run the actual biclustering algorithm.
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
private void	multipleNodeDeletion(double[][] mat, ChengAndChurch.BiclusterCandidate cand) Algorithm 2 of Cheng and Church.
private void	nodeAddition(double[][] mat, ChengAndChurch.BiclusterCandidate cand) Algorithm 3 of Cheng and Church.
private void	singleNodeDeletion(double[][] mat, ChengAndChurch.BiclusterCandidate cand) Algorithm 1 of Cheng and Church: Remove single rows or columns.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering

colsBitsetToIDs, colsBitsetToIDs, defineBicluster, defineBicluster, getColDim, getDatabase, getRelation, getRowDBID, getRowDim, rowsBitsetToIDs, rowsBitsetToIDs, run, valueAt

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

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

MIN_COLUMN_REMOVE_THRESHOLD

private static final int MIN_COLUMN_REMOVE_THRESHOLD

The minimum number of columns that the database must have so that a removal of columns is performed in multipleNodeDeletion(double[][], de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate).

Just start deleting multiple columns when more than 100 columns are in the data matrix.

See Also:

Constant Field Values

MIN_ROW_REMOVE_THRESHOLD

private static final int MIN_ROW_REMOVE_THRESHOLD

The minimum number of rows that the database must have so that a removal of rows is performed in multipleNodeDeletion(double[][], de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate).

Just start deleting multiple rows when more than 100 rows are in the data matrix.

See Also:

Constant Field Values

delta

private double delta

Threshold for the score.

alpha

private double alpha

The parameter for multiple node deletion.

It is used to magnify the delta value in the multipleNodeDeletion(double[][], de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate) method.

n

private int n

Number of biclusters to be found.

useinverted

private boolean useinverted

Allow inversion of rows in the last phase.

dist

private Distribution dist

Distribution to sample random replacement values from.

Constructor Detail

ChengAndChurch

public ChengAndChurch(double delta,
                      double alpha,
                      int n,
                      Distribution dist)

Constructor.

Parameters:

delta - Delta parameter: desired quality

alpha - Alpha parameter: controls switching to single node deletion approach

n - Number of clusters to detect

dist - Distribution of random values to insert

Method Detail

biclustering

public Clustering<BiclusterWithInversionsModel> biclustering()

Description copied from class: AbstractBiclustering

Run the actual biclustering algorithm.

This method is supposed to be called only from the method AbstractBiclustering.run(de.lmu.ifi.dbs.elki.database.relation.Relation<V>).

Specified by:

biclustering in class AbstractBiclustering<V extends NumberVector,BiclusterWithInversionsModel>

singleNodeDeletion

private void singleNodeDeletion(double[][] mat,
                                ChengAndChurch.BiclusterCandidate cand)

Algorithm 1 of Cheng and Church:

Remove single rows or columns.

Inverted rows are not supported in this method.

Parameters:

mat - Data matrix

cand - Bicluster candidate

multipleNodeDeletion

private void multipleNodeDeletion(double[][] mat,
                                  ChengAndChurch.BiclusterCandidate cand)

Algorithm 2 of Cheng and Church.

Remove all rows and columns that reduce the residue by alpha.

Inverted rows are not supported in this method.

Parameters:

mat - Data matrix

cand - Bicluster candidate

nodeAddition

private void nodeAddition(double[][] mat,
                          ChengAndChurch.BiclusterCandidate cand)

Algorithm 3 of Cheng and Church.

Try to re-add rows or columns that decrease the overall score.

Also try adding inverted rows.

Parameters:

mat - Data matrix

cand - Bicluster candidate

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<BiclusterWithInversionsModel>>

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<BiclusterWithInversionsModel>>

Returns:

the static logger