Plot importance heatmap for a view

Generate a heatmap with importances of predictor-target interaction.

Usage

plot_interaction_heatmap(
  misty.results,
  view,
  cutoff = 1,
  trim = -Inf,
  trim.measure = c("gain.R2", "multi.R2", "intra.R2", "gain.RMSE", "multi.RMSE",
    "intra.RMSE"),
  clean = FALSE
)

Arguments

misty.results

a results list generated by collect_results().

view

abbreviated name of the view.

cutoff

importance threshold. Importances below this value will be colored white in the heatmap and considered as not relevant.

trim

display targets with performance value above (if R2 or gain) or below (otherwise) this value only.

trim.measure

the measure used for trimming.

clean

a logical indicating whether to remove rows and columns with all importances are below cutoff from the heatmap.

Value

The misty.results list (invisibly).

See also

collect_results() to generate a results list from raw results.

Other plotting functions: plot_contrast_heatmap(), plot_contrast_results(), plot_improvement_stats(), plot_interaction_communities(), plot_view_contributions()

Examples

all.samples <- list.dirs("results", recursive = FALSE)

collect_results(all.samples) %>%
  plot_interaction_heatmap("intra") %>%
  plot_interaction_heatmap("para.10", cutoff = 0.5)
#> 
#> Collecting improvements
#> 
#> Collecting contributions
#> 
#> Collecting importances
#> 
#> Aggregating