FSelector (version 0.21)

cutoff: Cutoffs

Description

The algorithms select a subset from a ranked attributes.

Usage

cutoff.k(attrs, k)
cutoff.k.percent(attrs, k)
cutoff.biggest.diff(attrs)

Arguments

attrs

a data.frame containing ranks for attributes in the first column and their names as row names

k

a positive integer in case of cutoff.k and a numeric between 0 and 1 in case of cutoff.k.percent

Value

A character vector containing selected attributes.

Details

cutoff.k chooses k best attributes

cutoff.k.percent chooses best k * 100% of attributes

cutoff.biggest.diff chooses a subset of attributes which are significantly better than other.

Examples

# NOT RUN {
  data(iris)

  weights <- information.gain(Species~., iris)
  print(weights)

  subset <- cutoff.k(weights, 1)
  f <- as.simple.formula(subset, "Species")
  print(f)

  subset <- cutoff.k.percent(weights, 0.75)
  f <- as.simple.formula(subset, "Species")
  print(f)

  subset <- cutoff.biggest.diff(weights)
  f <- as.simple.formula(subset, "Species")
  print(f)
  
# }