Man pages for m-Py/anticlust
Subset Partitioning via Anticlustering
| anticlustering | Anticlustering |
| balanced_clustering | Create balanced clusters of equal size |
| bicriterion_anticlustering | Bicriterion iterated local search heuristic |
| categorical_sampling | Random sampling employing a categorical constraint |
| categories_to_binary | Get binary representation of categorical variables |
| dispersion_objective | Cluster dispersion |
| diversity_objective | (Anti)cluster editing "diversity" objective |
| fast_anticlustering | Fast anticlustering |
| generate_exchange_partners | Get exchange partners for fast_anticlustering() |
| generate_partitions | Generate all partitions of same cardinality |
| kplus_anticlustering | K-plus anticlustering |
| kplus_moment_variables | Compute k-plus variables |
| matching | Matching |
| mean_sd_tab | Means and standard deviations by group variable formatted in... |
| n_partitions | Number of equal sized partitions |
| optimal_anticlustering | Optimal ("exact") algorithms for anticlustering |
| optimal_dispersion | Maximize dispersion for K groups |
| plot_clusters | Visualize a cluster analysis |
| plot_similarity | Plot similarity objective by cluster |
| schaper2019 | Ratings for 96 words |
| three_phase_search_anticlustering | Three phase search with dynamic population size heuristic |
| variance_objective | Objective value for the variance criterion |
| wce | Exact weighted cluster editing |
