klaR (version 0.6-14)

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

sv

Scaled values

k

Optimal 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://hdl.handle.net/2003/2789

Examples

# NOT RUN {
library(MASS)
data(iris)
ldaobj <- lda(Species ~ ., data = iris)
ldapred <- predict(ldaobj)$posterior
e.scal(ldapred)
e.scal(ldapred, tc = iris$Species)
# }