| as.cl_addtree | Additive Tree Distances |
| as.cl_class_ids | Classes in a Partition |
| as.cl_dendrogram | Hierarchies |
| as.cl_ensemble | Cluster Ensembles |
| as.cl_hard_partition | Partitions |
| as.cl_hierarchy | Hierarchies |
| as.cl_membership | Memberships of Partitions |
| as.cl_partition | Partitions |
| as.cl_ultrametric | Ultrametrics of Hierarchies |
| Cassini | Cassini Data |
| CKME | Cassini Data Partitions Obtained by K-Means |
| cl_agreement | Agreement Between Partitions or Hierarchies |
| cl_bag | Bagging for Clustering |
| cl_boot | Bootstrap Resampling of Clustering Algorithms |
| cl_classes | Cluster Classes |
| cl_class_ids | Classes in a Partition |
| cl_consensus | Consensus Partitions and Hierarchies |
| cl_dendrogram | Hierarchies |
| cl_dissimilarity | Dissimilarity Between Partitions or Hierarchies |
| cl_ensemble | Cluster Ensembles |
| cl_fuzziness | Partition Fuzziness |
| cl_hard_partition | Partitions |
| cl_hierarchy | Hierarchies |
| cl_join | Cluster Lattices |
| cl_margin | Membership Margins |
| cl_medoid | Medoid Partitions and Hierarchies |
| cl_meet | Cluster Lattices |
| cl_membership | Memberships of Partitions |
| cl_object_names | Find Object Names |
| cl_pam | K-Medoids Partitions of Clusterings |
| cl_partition | Partitions |
| cl_pclust | Prototype-Based Partitions of Clusterings |
| cl_predict | Predict Memberships |
| cl_prototypes | Partition Prototypes |
| cl_tabulate | Tabulate Vector Objects |
| cl_ultrametric | Ultrametrics of Hierarchies |
| cl_validity | Validity Measures for Partitions and Hierarchies |
| cl_validity.default | Validity Measures for Partitions and Hierarchies |
| GVME | Gordon-Vichi Macroeconomic Partition Ensemble Data |
| GVME_Consensus | Gordon-Vichi Macroeconomic Consensus Partition Data |
| is.cl_dendrogram | Hierarchies |
| is.cl_ensemble | Cluster Ensembles |
| is.cl_hard_partition | Partitions |
| is.cl_hierarchy | Hierarchies |
| is.cl_partition | Partitions |
| is.cl_soft_partition | Partitions |
| Kinship82 | Rosenberg-Kim Kinship Terms Partition Data |
| Kinship82_Consensus | Gordon-Vichi Kinship82 Consensus Partition Data |
| kmedoids | K-Medoids Clustering |
| l1_fit_ultrametric | Least Absolute Deviation Fit of Ultrametrics to Dissimilarities |
| l1_fit_ultrametric_target | Fit Dissimilarities to a Hierarchy |
| ls_fit_addtree | Least Squares Fit of Additive Tree Distances to Dissimilarities |
| ls_fit_centroid | Least Squares Fit of Additive Tree Distances to Dissimilarities |
| ls_fit_sum_of_ultrametrics | Least Squares Fit of Sums of Ultrametrics to Dissimilarities |
| ls_fit_ultrametric | Least Squares Fit of Ultrametrics to Dissimilarities |
| ls_fit_ultrametric_target | Fit Dissimilarities to a Hierarchy |
| n_of_classes | Classes in a Partition |
| n_of_objects | Number of Objects in a Partition or Hierarchy |
| Ops.cl_dendrogram | Cluster Lattices |
| Ops.cl_hierarchy | Cluster Lattices |
| Ops.cl_partition | Cluster Lattices |
| pclust | Prototype-Based Partitioning |
| pclust_family | Prototype-Based Partitioning |
| pclust_object | Prototype-Based Partitioning |
| Phonemes | Miller-Nicely Consonant Phoneme Confusion Data |
| plot.cl_dendrogram | Hierarchies |
| solve_LSAP | Solve Linear Sum Assignment Problem |
| Summary.cl_hierarchy | Cluster Lattices |
| Summary.cl_partition | Cluster Lattices |
| sumt | Sequential Unconstrained Minimization Technique |