klaR (version 0.3-0)

e.scal: Function to calculate e- or softmax scaled membership values

Description

Calculates the e- or softmax scaled membership values of an argmax based classification rule.

Usage

e.scal(x, k = 1, tc = NULL)

Arguments

x
matrix of membership values
k
parameter for e-scaling (1 for softmax)
tc
vector of true classes (required if k has to be optimized)

Value

  • A list containing elements
  • svScaled values
  • kOptimal k

Details

For any membership vector y $\exp(y\cdot k) / \sum\exp(y\cdot k)$ is calculated. If k=1, the classical softmax scaling is used. If the true classes are given, k is optimized so that the apparent error rate is minimized.

References

Garczarek, Ursula Maria (2002): Classification rules in standardized partition spaces. Dissertation, University of Dortmund. URL http://eldorado.uni-dortmund.de:8080/FB5/ls7/forschung/2002/Garczarek

Examples

Run this code
library(MASS)
data(iris)
ldaobj <- lda(Species ~ ., data = iris)
ldapred <- predict(ldaobj)$posterior
e.scal(ldapred)
e.scal(ldapred, tc = iris$Species)

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