# A regression model predicting ozone levels
data(airquality)
ozone.rp <- rfPermute(Ozone ~ ., data = airquality, na.action = na.omit, ntree = 100, num.rep = 50)
ozone.rp
# Plot the scaled importance distributions
# Significant (p <= 0.05) predictors are in red
plotImportance(ozone.rp, scale = TRUE)
# Plot the importance null distributions and observed values for two of the predictors
plotNull(ozone.rp, preds = c("Solar.R", "Month"))
# A classification model classifying cars to manual or automatic transmission
data(mtcars)
am.rp <- rfPermute(factor(am) ~ ., mtcars, ntree = 100, num.rep = 50)
summary(am.rp)
plotImportance(am.rp, scale = TRUE, sig.only = TRUE)
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