Package edu.cmu.tetrad.search

Class BuildPureClusters

java.lang.Object

edu.cmu.tetrad.search.BuildPureClusters

public final class BuildPureClusters
extends Object

BuildPureClusters is an implementation of the automated clustering and purification methods described on the report "Learning Measurement Models" CMU-CALD-03-100.

The output is only the purified model. Future versions may include options to visualize the measurement pattern in the GUI (it shows up in the console window, though.)

No background knowledge is allowed yet. Future versions of this algorithm will include it.

References:

Silva, R.; Scheines, R.; Spirtes, P.; Glymour, C. (2003). "Learning measurement models". Technical report CMU-CALD-03-100, Center for Automated Learning and Discovery, Carnegie Mellon University.

Bollen, K. (1990). "Outlier screening and distribution-free test for vanishing tetrads." Sociological Methods and Research 19, 80-92.

Wishart, J. (1928). "Sampling errors in the theory of two factors". British Journal of Psychology 19, 180-187.

Bron, C. and Kerbosch, J. (1973) "Algorithm 457: Finding all cliques of an undirected graph". Communications of ACM 16, 575-577.

--Cleaned up by jdramsey 2022-03-28

Author:

Ricardo Silva

Constructor Summary

Constructors

Constructor	Description
BuildPureClusters(CovarianceMatrix covarianceMatrix, double alpha, TestType sigTestType)
BuildPureClusters(DataSet dataSet, double alpha, TestType sigTestType)
BuildPureClusters(ICovarianceMatrix covarianceMatrix, double alpha, TestType sigTestType)	Constructor BuildPureClusters

Method Summary

Modifier and Type	Method	Description
ICovarianceMatrix	getCovarianceMatrix()	Data storage
IndependenceTest	getIndependenceTest()
boolean	isVerbose()
int	numVariables()
Graph	search()
void	setCheckType(ClusterSignificance.CheckType checkType)
void	setVerbose(boolean verbose)

Methods inherited from class java.lang.Object

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

Constructor Details

BuildPureClusters

public BuildPureClusters(ICovarianceMatrix covarianceMatrix,
 double alpha,
 TestType sigTestType)

Constructor BuildPureClusters

BuildPureClusters

public BuildPureClusters(CovarianceMatrix covarianceMatrix,
 double alpha,
 TestType sigTestType)

BuildPureClusters

public BuildPureClusters(DataSet dataSet,
 double alpha,
 TestType sigTestType)

Method Details

search

public Graph search()

Returns:

the result search graph, or null if there is no model.

getCovarianceMatrix

public ICovarianceMatrix getCovarianceMatrix()

Data storage

numVariables

public int numVariables()

getIndependenceTest

public IndependenceTest getIndependenceTest()

setVerbose

public void setVerbose(boolean verbose)

isVerbose

public boolean isVerbose()

setCheckType

public void setCheckType(ClusterSignificance.CheckType checkType)