softmaxnorm: Softmax Normalization

Description

This is a function that applies softmax normalization to a matrix or dataframe.

Usage

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Arguments

data

The datset to be normalized

Details

This normalization is so called because it reaches "softly" towards maximum and minimum value, never quite getting there. The transformation is more or less linear in the middle range, and has a nonlinearity at both ends. The output range covered is [0,1]. The algorithm removes the classes of the dataset before normalization and replaces them at the end to form the matrix again.

Value

softdata

original matrix normalized

Author(s)

Caroline Rodriguez and Edgar Acuna

Examples

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#---- Softmax Normalization----
data(sonar)
sonar.sftnorm=softmaxnorm(sonar)
op=par(mfrow=c(2,1))
plot(sonar[,1])
plot(sonar.sftnorm[,1])
par(op)

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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