Evolutionary Search for Optimal Node Combinations in Trees
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Documentation for package ‘treehunt’ version 0.0.2
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| aggregate_ga_results | Aggregate GA Results from Multiple JSON Files returned by run_ga_batch |
| clustering_genetic_algorithm | Clustering of a Cocktail List using DBSCAN on UMAP Projection |
| compute_score | Compute scores for supplied node combinations |
| decode_treehunt_solutions | Decode treehunt node indexes |
| filter_out_cocktails | Filter a list of cocktails accoring to the mean depth of nodes inside each cocktail. A cocktail is kept if the mean depth of his nodes is greater than 'mean_depth_cocktail' (default = 3). This function aim is to provide more interpretable cocktail to the user. |
| fit_pwp_rao_context | Fit the reduced PWP model and prepare a Rao-score context |
| get_dissimilarity_of_list | Compute the dissimilarity matrix on a list of cocktails |
| get_taker | Identify observations covered by hierarchical combinations |
| map_cocktail_names | Map Cocktail Indices to Names Saved GA combinations use zero-based node indices; tree rows use one-based indices. |
| mcmc_size_2_true_score_distribution | Run MCMC Algorithm to Compute the Score Distribution Among Node Combinations of Size 2 |
| plot_ga_clusters | Plot GA Clustering Results |
| print.pwp_rao_context | Fit the reduced PWP model and prepare a Rao-score context |
| process_ga_scores | Process and Attach GA Scores and Statistics (Generic) |
| refit_pwp_combinations | Refit selected combinations with patient-clustered Cox models |
| run_ga_batch | Run Multiple Genetic Algorithm Replicates from Configuration |
| run_genetic_algorithm | Run Genetic Algorithm for High Score Nodes Combination Search |
| run_genetic_algorithm_df_tree | Run Genetic Algorithm for High Score Nodes Combination Search |
| run_mcmc | Run MCMC Algorithm for Estimation of Score Distribution Among Nodes of The Tree |
| run_mcmc_df_tree | Run MCMC Algorithm for Estimation of Score Distribution Among Nodes of The Tree |
| run_pwp_genetic_algorithm | Run the genetic algorithm with the PWP Rao fitness |
| run_pwp_mcmc | Run MCMC with the PWP Rao fitness |
| score_pwp_combinations | Evaluate full Rao statistics for combinations |
| summarize_ga_pipeline | Complete GA Results Analysis Pipeline (Generic) |
| uniform_score_reference | Recover the uniform score reference from a tempered MCMC trajectory |
| weight_ess | Effective sample size based on importance weights |