| Abstract optimization algorithm class | Alg-class |
| Display the list of every currently available optimization algorithm | available_algorithms |
| Display the list of every currently available DLVM | available_models |
| Books about US politics network dataset | Books |
| Method to extract the clustering results from an 'IclFit-class' object | clustering clustering,IclFit-method |
| Extract parameters from an 'DcLbmFit-class' object | coef,DcLbmFit-method |
| Extract parameters from an 'DcSbmFit-class' object | coef,DcSbmFit-method |
| Extract mixture parameters from 'DiagGmmFit-class' object | coef,DiagGmmFit-method |
| Extract mixture parameters from 'GmmFit-class' object | coef,GmmFit-method |
| Extract parameters from an 'IclFit-class' object | coef,IclFit-method |
| Extract parameters from an 'LcaFit-class' object | coef,LcaFit-method |
| Extract parameters from an 'MoMFit-class' object | coef,MoMFit-method |
| Extract mixture parameters from 'MoRFit-class' object using MAP estimation | coef,MoRFit-method |
| Extract parameters from an 'MultSbmFit-class' object | coef,MultSbmFit-method |
| Extract parameters from an 'SbmFit-class' object | coef,SbmFit-method |
| Combined Models classes | CombinedModels CombinedModels-class |
| Combined Models fit results class | CombinedModelsFit-class |
| Combined Models hierarchical fit results class | CombinedModelsPath-class |
| Method to cut a DcLbmPath solution to a desired number of cluster | cut,DcLbmPath-method |
| Generic method to cut a path solution to a desired number of cluster | cut,IclPath-method |
| Degree Corrected Latent Block Model for bipartite graph class | DcLbm DcLbm-class DcLbmPrior DcLbmPrior-class |
| Degree corrected Latent Block Model fit results class | DcLbmFit-class |
| Degree corrected Latent Block Model hierarchical fit results class | DcLbmPath-class |
| Degree Corrected Stochastic Block Model Prior class | DcSbm DcSbm-class DcSbmPrior DcSbmPrior-class |
| Degree Corrected Stochastic Block Model fit results class | DcSbmFit-class |
| Degree Corrected Stochastic Block Model hierarchical fit results class | DcSbmPath-class |
| Diagonal Gaussian Mixture Model Prior description class | DiagGmm DiagGmm-class DiagGmmPrior DiagGmmPrior-class |
| Diagonal Gaussian mixture model fit results class | DiagGmmFit-class |
| Diagonal Gaussian mixture model hierarchical fit results class | DiagGmmPath-class |
| Abstract class to represent a generative model for co-clustering | DlvmCoPrior-class |
| Abstract class to represent a generative model for clustering | DlvmPrior-class |
| Extract a part of a 'CombinedModelsPath-class' object | extractSubModel extractSubModel,CombinedModelsPath,character-method |
| Fashion mnist dataset | fashion |
| Fifa data | Fifa |
| American College football network dataset | Football |
| Genetic optimization algorithm | Genetic Genetic-class |
| Gaussian Mixture Model Prior description class | Gmm Gmm-class GmmPrior GmmPrior-class |
| Gaussian mixture model fit results class | GmmFit-class |
| Make a matrix of plots with a given data and gmm fitted parameters | gmmpairs |
| Gaussian mixture model hierarchical fit results class | GmmPath-class |
| Model based hierarchical clustering | greed-package greed |
| Compute the entropy of a discrete sample | H |
| Hybrid optimization algorithm | Hybrid Hybrid-class |
| Generic method to extract the ICL value from an 'IclFit-class' object | ICL ICL,IclFit-method |
| Abstract class to represent a clustering result | IclFit-class |
| Abstract class to represent a hierarchical clustering result | IclPath-class |
| Jazz musicians network dataset | Jazz |
| Generic method to get the number of clusters from an 'IclFit-class' object | K K,IclFit-method |
| Latent Class Analysis Model Prior class | Lca Lca-class LcaPrior LcaPrior-class |
| Latent Class Analysis fit results class | LcaFit-class |
| Latent Class Analysis hierarchical fit results class | LcaPath-class |
| Compute the mutual information of two discrete samples | MI |
| Mixture of Multinomial Model Prior description class | MoM MoM-class MoMPrior MoMPrior-class |
| Mixture of Multinomial fit results class | MoMFit-class |
| Mixture of Multinomial hierarchical fit results class | MoMPath-class |
| Multivariate mixture of regression Prior model description class | MoR MoR-class MoRPrior MoRPrior-class |
| Clustering with a multivariate mixture of regression model fit results class | MoRFit-class |
| Multivariate mixture of regression model hierarchical fit results class | MoRPath-class |
| Greedy algorithm with multiple start class | Multistarts Multistarts-class |
| Multinomial Stochastic Block Model Prior class | MultSbm MultSbm-class MultSbmPrior MultSbmPrior-class |
| Multinomial Stochastic Block Model fit results class | MultSbmFit-class |
| Multinomial Stochastic Block Model hierarchical fit results class | MultSbmPath-class |
| Mushroom data | mushroom |
| Ndrangheta mafia covert network dataset | Ndrangheta |
| NewGuinea data | NewGuinea |
| Compute the normalized mutual information of two discrete samples | NMI |
| Plot a 'DcLbmFit-class' | plot,DcLbmFit,missing-method |
| Plot a 'DcLbmPath-class' | plot,DcLbmPath,missing-method |
| Plot a 'DcSbmFit-class' object | plot,DcSbmFit,missing-method |
| Plot a 'DiagGmmFit-class' object | plot,DiagGmmFit,missing-method |
| Plot a 'GmmFit-class' object | plot,GmmFit,missing-method |
| Plot an 'IclPath-class' object | plot,IclPath,missing-method |
| Plot a 'LcaFit-class' object | plot,LcaFit,missing-method |
| Plot a 'MoMFit-class' object | plot,MoMFit,missing-method |
| Plot a 'MultSbmFit-class' object | plot,MultSbmFit,missing-method |
| Plot a 'SbmFit-class' object | plot,SbmFit,missing-method |
| Generic method to extract the prior used to fit 'IclFit-class' object | prior prior,IclFit-method |
| Generates graph adjacency matrix using a degree corrected SBM | rdcsbm |
| Generate a data matrix using a Latent Block Model | rlbm |
| Generate data from lca model | rlca |
| Generate data using a Multinomial Mixture | rmm |
| Generate data from a mixture of regression model | rmreg |
| Generate a graph adjacency matrix using a Stochastic Block Model | rmultsbm |
| Generate a graph adjacency matrix using a Stochastic Block Model | rsbm |
| Stochastic Block Model Prior class | Sbm Sbm-class SbmPrior SbmPrior-class |
| Stochastic Block Model fit results class | SbmFit-class |
| Stochastic Block Model hierarchical fit results class | SbmPath-class |
| Greedy algorithm with seeded initialization | Seed Seed-class |
| SevenGraders data | SevenGraders |
| Show an IclPath object | show,IclFit-method |
| Regularized spectral clustering | spectral |
| Convert a binary adjacency matrix with missing value to a cube | to_multinomial |
| Young People survey data | Youngpeoplesurvey |
