Clustering and Model Selection with the Integrated Classification Likelihood


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Documentation for package ‘greed’ version 0.5.1

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alg-class Abstract optimization algorithm class
Blogs Political blogs network dataset
Books Books about US politics network dataset
coef-method Extract parameters from an 'co_dcsbm_fit-class' object
coef-method Extract parameters from an 'dcsbm_fit-class' object
coef-method Extract mixture parameters from 'diaggmm_fit-class' object
coef-method Extract mixture parameters from 'gmm_fit-class' object
coef-method Extract parameters from an 'misssbm_fit-class' object
coef-method Extract parameters from an 'mm_fit-class' object
coef-method Extract parameters from an 'multsbm_fit-class' object
coef-method Extract mixture parameters from 'mvmreg_fit-class' object
coef-method Extract parameters from an 'sbm_fit-class' object
co_dcsbm-class Degree Corrected Stochastic Block Model for bipartite graph class
co_dcsbm_fit-class Degree corrected stochastic block model for bipartite graph fit results class
co_dcsbm_path-class Degree corrected stochastic block model for bipartite graph hierarchical fit results class
cut-method method to cut a path solution to a desired number of cluster
cut-method Method to cut a path solution to a desired number of cluster
dcsbm-class Degree Corrected Stochastic Block Model class
dcsbm_fit-class Degree Corrected Stochastic Block Model fit results class
dcsbm_path-class Degree Corrected Stochastic Block Model hierarchical fit results class
diaggmm-class Diagonal Gaussian mixture model description class
diaggmm_fit-class Diagonal Gaussian mixture model fit results class
diaggmm_path-class Diagonal Gaussian mixture model hierarchical fit results class
fashion Fashion mnist dataset
Football American College football network dataset
FrenchParliament French Parliament votes dataset
genetic-class Genetic optimization algorithm
gmm-class Gaussian mixture model description class
gmmpairs Make a matrix of plots with a given data and gmm fitted parameters
gmm_fit-class Gaussian mixture model fit results class
gmm_path-class Gaussian mixture model hierarchical fit results class
graph_balance graph_balance
greed Model based hierarchical clustering
greed_cond Conditional model based hierarchical clustering
H Compute the entropy of a discrete sample
hybrid-class Hybrid optimization algorithm
icl_fit-class abstract class to represent a clustering result
icl_model-class abstract class to represent a generative model An S4 class to represent an abstract generative model
icl_path-class abstract class to represent a hierarchical clustering result
Jazz Jazz musicians network dataset
Jazz_full Jazz musicians / Bands relations
MI Compute the mutual information of two discrete samples
misssbm-class Stochastic Block Model with sampling scheme class
misssbm_fit-class Stochastic Block Model with sampling scheme fit results class
misssbm_path-class Stochastic Block Model with sampling scheme hierarchical fit results class
mm-class Mixture of Multinomial model description class
mm_fit-class Mixture of Multinomial fit results class
mm_path-class Mixture of Multinomial hierarchical fit results class
multistarts-class Greedy algorithm with multiple start class
multsbm-class Multinomial Stochastic Block Model class
multsbm_fit-class Multinomial Stochastic Block Model fit results class
multsbm_path-class Multinomial Stochastic Block Model hierachical fit results class
mvmreg-class Multivariate mixture of regression model description class
mvmreg_fit-class Clustering with a multivariate mixture of regression model fit results class
mvmreg_path-class Multivariate mixture of regression model hierarchical fit results class
NMI Compute the normalized mutual information of two discrete samples
nodelinklab nodelinklab
plot-method plot a 'co_dcsbm_fit-class'
plot-method plot a 'co_dcsbm_path-class'
plot-method plot a 'sbm_fit-class' object
plot-method plot a 'sbm_path-class' object
plot-method plot a 'diaggmm_path-class' object
plot-method plot a 'gmm_path-class' object
plot-method plot a 'misssbm_fit-class' object
plot-method plot a 'misssbm_path-class' object
plot-method plot a 'mm_fit-class' object
plot-method plot a 'mm_path-class' object
plot-method plot a 'multsbm_fit-class' object
plot-method plot a 'sbm_path-class' object
plot-method plot a 'mvmreg_path-class' object
plot-method plot a 'sbm_fit-class' object
plot-method plot a 'sbm_path-class' object
print-method print an icl_path object
rdcsbm Generates graph adjacency matrix using a degree corrected SBM
rlbm Generate a data matrix using a Latent Block Model
rmm Generate data using a Multinomial Mixture
rmreg Generate data from a mixture of regression model
rmultsbm Generate a graph adjacency matrix using a Stochastic Block Model
rsbm Generate a graph adjacency matrix using a Stochastic Block Model
sbm-class Stochastic Block Model class
sbm_fit-class Stochastic Block Model fit results class
sbm_path-class Stochastic Block Model hierarchical fit results class
seed-class Greedy algorithm with seeded initialization
spectral Regularized spectral clustering
to_multinomial Convert a binary adjacency matrix with missing value to a cube
Xvlegislature French Parliament votes dataset