plot_interaction_heatmap {mistyR} | R Documentation

## Plot importance heatmap for a view

### Description

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)

[Package mistyR version 1.2.1 Index]