Plot Random Forest Importance Distributions
Plot the Random Forest importance distributions, with significant p-values as estimated in rfPermute.
## S3 method for class 'rp.importance' plot( x, alpha = 0.05, sig.only = FALSE, type = NULL, n = NULL, main = NULL, ... )
x |
An object produced by a call to |
alpha |
Critical alpha to identify "significant" predictors. |
sig.only |
Plot only the significant (<= |
type |
character vector listing which importance measures to plot.
Can be class names or names of overall importance measures
(e.g., "MeanDecreaseAccuracy") in the |
n |
Plot |
main |
Main title for plot. |
... |
Optional arguments which will be ignored. |
The function will generate a panel of plots, one for each importance type.
Eric Archer eric.archer@noaa.gov
# A regression model using the ozone example data(airquality) ozone.rfP <- rfPermute( Ozone ~ ., data = airquality, ntree = 100, na.action = na.omit, nrep = 50, num.cores = 1 ) # Plot the unscaled importance distributions and highlight significant predictors plot(rp.importance(ozone.rfP, scale = FALSE)) # ... and the scaled measures plot(rp.importance(ozone.rfP, scale = TRUE))
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