Uses of Package
edu.cmu.tetrad.search.unmix

Packages that use edu.cmu.tetrad.search.unmix

Package	Description
edu.cmu.tetrad.search.unmix

Classes in edu.cmu.tetrad.search.unmix used by edu.cmu.tetrad.search.unmix

Class	Description
CausalUnmixer.Config	The Config class encapsulates the configuration settings used for the unmixing or clustering process within the CausalUnmixer framework.
EmUnmix.Config	Configuration class for the EmUnmix algorithm, providing parameters and settings to control the behavior of the unmixing process.
GaussianMixtureEM.Config	Configuration class for the Gaussian Mixture Model (GMM) Expectation-Maximization (EM) algorithm.
GaussianMixtureEM.CovarianceType	Specifies the type of covariance matrix used in the Gaussian Mixture Model (GMM) implemented by the GaussianMixtureEM class.
GaussianMixtureEM.Model	Represents the Gaussian Mixture Model (GMM) computed and used in the GaussianMixtureEM class.
KMeans.Result	Represents the result of a clustering operation using the KMeans algorithm.
LinearQRRegressor	Linear regression using EJML's QR-based solve (stable).
ParentSupersetBuilder.Config	Represents the configuration settings used for statistical screening and optional bagging operations in the parent superset construction process.
ParentSupersetBuilder.ScoreType	Represents the type of correlation score used for statistical calculations or comparisons.
ResidualRegressor	Interface for local regressors used to compute residual signatures: X ~ f(Pa).
UnmixDiagnostics.BicDelta	Represents the Bayesian Information Criterion (BIC) values for mixture models with K=1 and K=2 clusters and the difference (delta) between these values.
UnmixDiagnostics.EntropyStats	Represents the entropy statistics of clustering results in the context of mixture models.
UnmixDiagnostics.GraphDiff	Represents the difference between two clustering graphs in terms of structural and adjacency metrics.
UnmixDiagnostics.StabilityResult	Represents the result of a stability analysis of clustering, typically performed by evaluating the Adjusted Rand Index (ARI) across multiple independent runs.
UnmixResult	Container for unmixing output (labels, per-cluster datasets, optional graphs).