plot.VarImp: Variable Importance Plot

In ODRF: Oblique Decision Random Forest for Classification and Regression

Variable Importance Plot

Description

Dotchart of variable importance as measured by an Oblique Decision Random Forest.

Usage

## S3 method for class 'VarImp'
plot(x, nvar = min(30, nrow(x$varImp)), digits = NULL, main = NULL, ...)

Arguments

x	An object of class VarImp.
nvar	number of variables to show.
digits	Integer indicating the number of decimal places (round) or significant digits (signif) to be used.
main	plot title.
...	Arguments to be passed to methods.

Value

The horizontal axis is the increased error of ODRF after replacing the variable, the larger the increased error the more important the variable is.

See Also

ODRF VarImp

Examples

data(breast_cancer)
set.seed(221212)
train <- sample(1:569, 200)
train_data <- data.frame(breast_cancer[train, -1])
forest <- ODRF(train_data[, -1], train_data[, 1], split = "gini",
  parallel = FALSE)
varimp <- VarImp(forest, train_data[, -1], train_data[, 1])
plot(varimp)

ODRF documentation built on May 31, 2023, 8:22 p.m.