random.forest.importance: RandomForest filter

In FSelector: Selecting Attributes

RandomForest filter

Description

The algorithm finds weights of attributes using RandomForest algorithm.

Usage

random.forest.importance(formula, data, importance.type = 1)

Arguments

formula	a symbolic description of a model
data	data to process
importance.type	either 1 or 2, specifying the type of importance measure (1=mean decrease in accuracy, 2=mean decrease in node impurity)

Details

This is a wrapper for importance.

Value

a data.frame containing the worth of attributes in the first column and their names as row names

Author(s)

Piotr Romanski

Examples

  library(mlbench)
  data(HouseVotes84)
  
  weights <- random.forest.importance(Class~., HouseVotes84, importance.type = 1)
  print(weights)
  subset <- cutoff.k(weights, 5)
  f <- as.simple.formula(subset, "Class")
  print(f)

FSelector documentation built on Aug. 23, 2023, 1:08 a.m.