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rfPermute (version 2.5.2)

plotNull: Plot Random Forest Importance Null Distributions

Description

Plot the Random Forest null distributions importance metrics, observed values, and p-values for each predictor variable from the object produced by a call to rfPermute.

Usage

plotNull(
  x,
  preds = NULL,
  imp.type = NULL,
  scale = TRUE,
  plot.type = c("density", "hist"),
  plot = TRUE
)

Value

A named list of the ggplot figures produced is invisibly returned.

Arguments

x

An object produced by a call to rfPermute.

preds

a character vector of predictors to plot. If NULL, then all predictors are plotted.

imp.type

A character vector giving the importance metric(s) to plot.

scale

Plot importance measures scaled (divided by) standard errors?

plot.type

type of plot to produce: "density" for smoothed density plot, or "hist" for histogram.

plot

display the plot?

Author

Eric Archer eric.archer@noaa.gov

Details

The function will generate an plot for each predictor, with facetted importance metrics. The vertical red line shows the observed importance score and the _p_-value is given in the facet label.

Examples

Run this code
# A regression model using the ozone example
data(airquality)
ozone.rp <- rfPermute(
  Ozone ~ ., data = airquality, ntree = 100, 
  na.action = na.omit, nrep = 50, num.cores = 1
)
  
# Plot the null distributions and observed values.
plotNull(ozone.rp) 

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