A B C D E F G H I J K L M N P R S T Y
Alg-class | Abstract optimization algorithm class |
available_algorithms | Display the list of every currently available optimization algorithm |
available_models | Display the list of every currently available DLVM |
Books | Books about US politics network dataset |
clustering | Method to extract the clustering results from an 'IclFit-class' object |
clustering-method | Method to extract the clustering results from an 'IclFit-class' object |
coef-method | Extract parameters from an 'DcLbmFit-class' object |
coef-method | Extract parameters from an 'DcSbmFit-class' object |
coef-method | Extract mixture parameters from 'DiagGmmFit-class' object |
coef-method | Extract mixture parameters from 'GmmFit-class' object |
coef-method | Extract parameters from an 'IclFit-class' object |
coef-method | Extract parameters from an 'LcaFit-class' object |
coef-method | Extract parameters from an 'MoMFit-class' object |
coef-method | Extract mixture parameters from 'MoRFit-class' object using MAP estimation |
coef-method | Extract parameters from an 'MultSbmFit-class' object |
coef-method | Extract parameters from an 'SbmFit-class' object |
CombinedModels | Combined Models classes |
CombinedModels-class | Combined Models classes |
CombinedModelsFit-class | Combined Models fit results class |
CombinedModelsPath-class | Combined Models hierarchical fit results class |
cut-method | Method to cut a DcLbmPath solution to a desired number of cluster |
cut-method | Generic method to cut a path solution to a desired number of cluster |
DcLbm | Degree Corrected Latent Block Model for bipartite graph class |
DcLbm-class | Degree Corrected Latent Block Model for bipartite graph class |
DcLbmFit-class | Degree corrected Latent Block Model fit results class |
DcLbmPath-class | Degree corrected Latent Block Model hierarchical fit results class |
DcLbmPrior | Degree Corrected Latent Block Model for bipartite graph class |
DcLbmPrior-class | Degree Corrected Latent Block Model for bipartite graph class |
DcSbm | Degree Corrected Stochastic Block Model Prior class |
DcSbm-class | Degree Corrected Stochastic Block Model Prior class |
DcSbmFit-class | Degree Corrected Stochastic Block Model fit results class |
DcSbmPath-class | Degree Corrected Stochastic Block Model hierarchical fit results class |
DcSbmPrior | Degree Corrected Stochastic Block Model Prior class |
DcSbmPrior-class | Degree Corrected Stochastic Block Model Prior class |
DiagGmm | Diagonal Gaussian Mixture Model Prior description class |
DiagGmm-class | Diagonal Gaussian Mixture Model Prior description class |
DiagGmmFit-class | Diagonal Gaussian mixture model fit results class |
DiagGmmPath-class | Diagonal Gaussian mixture model hierarchical fit results class |
DiagGmmPrior | Diagonal Gaussian Mixture Model Prior description class |
DiagGmmPrior-class | Diagonal Gaussian Mixture Model Prior description class |
DlvmCoPrior-class | Abstract class to represent a generative model for co-clustering |
DlvmPrior-class | Abstract class to represent a generative model for clustering |
extractSubModel | Extract a part of a 'CombinedModelsPath-class' object |
extractSubModel-method | Extract a part of a 'CombinedModelsPath-class' object |
fashion | Fashion mnist dataset |
Fifa | Fifa data |
Football | American College football network dataset |
Genetic | Genetic optimization algorithm |
Genetic-class | Genetic optimization algorithm |
Gmm | Gaussian Mixture Model Prior description class |
Gmm-class | Gaussian Mixture Model Prior description class |
GmmFit-class | Gaussian mixture model fit results class |
gmmpairs | Make a matrix of plots with a given data and gmm fitted parameters |
GmmPath-class | Gaussian mixture model hierarchical fit results class |
GmmPrior | Gaussian Mixture Model Prior description class |
GmmPrior-class | Gaussian Mixture Model Prior description class |
greed | Model based hierarchical clustering |
H | Compute the entropy of a discrete sample |
Hybrid | Hybrid optimization algorithm |
Hybrid-class | Hybrid optimization algorithm |
ICL | Generic method to extract the ICL value from an 'IclFit-class' object |
ICL-method | Generic method to extract the ICL value from an 'IclFit-class' object |
IclFit-class | Abstract class to represent a clustering result |
IclPath-class | Abstract class to represent a hierarchical clustering result |
Jazz | Jazz musicians network dataset |
K | Generic method to get the number of clusters from an 'IclFit-class' object |
K-method | Generic method to get the number of clusters from an 'IclFit-class' object |
Lca | Latent Class Analysis Model Prior class |
Lca-class | Latent Class Analysis Model Prior class |
LcaFit-class | Latent Class Analysis fit results class |
LcaPath-class | Latent Class Analysis hierarchical fit results class |
LcaPrior | Latent Class Analysis Model Prior class |
LcaPrior-class | Latent Class Analysis Model Prior class |
MI | Compute the mutual information of two discrete samples |
MoM | Mixture of Multinomial Model Prior description class |
MoM-class | Mixture of Multinomial Model Prior description class |
MoMFit-class | Mixture of Multinomial fit results class |
MoMPath-class | Mixture of Multinomial hierarchical fit results class |
MoMPrior | Mixture of Multinomial Model Prior description class |
MoMPrior-class | Mixture of Multinomial Model Prior description class |
MoR | Multivariate mixture of regression Prior model description class |
MoR-class | Multivariate mixture of regression Prior model description class |
MoRFit-class | Clustering with a multivariate mixture of regression model fit results class |
MoRPath-class | Multivariate mixture of regression model hierarchical fit results class |
MoRPrior | Multivariate mixture of regression Prior model description class |
MoRPrior-class | Multivariate mixture of regression Prior model description class |
Multistarts | Greedy algorithm with multiple start class |
Multistarts-class | Greedy algorithm with multiple start class |
MultSbm | Multinomial Stochastic Block Model Prior class |
MultSbm-class | Multinomial Stochastic Block Model Prior class |
MultSbmFit-class | Multinomial Stochastic Block Model fit results class |
MultSbmPath-class | Multinomial Stochastic Block Model hierarchical fit results class |
MultSbmPrior | Multinomial Stochastic Block Model Prior class |
MultSbmPrior-class | Multinomial Stochastic Block Model Prior class |
mushroom | Mushroom data |
Ndrangheta | Ndrangheta mafia covert network dataset |
NewGuinea | NewGuinea data |
NMI | Compute the normalized mutual information of two discrete samples |
plot-method | Plot a 'DcLbmFit-class' |
plot-method | Plot a 'DcLbmPath-class' |
plot-method | Plot a 'DcSbmFit-class' object |
plot-method | Plot a 'DiagGmmFit-class' object |
plot-method | Plot a 'GmmFit-class' object |
plot-method | Plot an 'IclPath-class' object |
plot-method | Plot a 'LcaFit-class' object |
plot-method | Plot a 'MoMFit-class' object |
plot-method | Plot a 'MultSbmFit-class' object |
plot-method | Plot a 'SbmFit-class' object |
prior | Generic method to extract the prior used to fit 'IclFit-class' object |
prior-method | Generic method to extract the prior used to fit 'IclFit-class' object |
rdcsbm | Generates graph adjacency matrix using a degree corrected SBM |
rlbm | Generate a data matrix using a Latent Block Model |
rlca | Generate data from lca 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 | Stochastic Block Model Prior class |
Sbm-class | Stochastic Block Model Prior class |
SbmFit-class | Stochastic Block Model fit results class |
SbmPath-class | Stochastic Block Model hierarchical fit results class |
SbmPrior | Stochastic Block Model Prior class |
SbmPrior-class | Stochastic Block Model Prior class |
Seed | Greedy algorithm with seeded initialization |
Seed-class | Greedy algorithm with seeded initialization |
SevenGraders | SevenGraders data |
show-method | Show an IclPath object |
spectral | Regularized spectral clustering |
to_multinomial | Convert a binary adjacency matrix with missing value to a cube |
Youngpeoplesurvey | Young People survey data |