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 |