signorm: Sigmoidal Normalization
In dprep: Data Pre-Processing and Visualization Functions for Classification

Description Usage Arguments Details Value Author(s) References Examples

Function that performs sigmoidal normalization.

1	signorm(data)

data

The dataset to be normalized, including classes

This method transforms the input data nonlinearly into [-1,1] using a sigmoid function. The original data is first centered about the mean, and then mapped to the almost linear region of the sigmoid. Is especially appropriate when outlying values are present.

Removes classes before normalization, and returns the normalized data set complete with classes rejoined.

sigdata

Original dataset normalized

Caroline Rodriguez and Edgar Acuna

Hann, J., Kamber, M. (2000). Data Mining: Concepts and Techniques. Morgan Kaufman Publishers.

#---- Sigmoidal Normalization ---
data(vehicle)
vehicle.signorm=signorm(vehicle)
op=par(mfrow=c(2,1))
plot(vehicle[,1])
plot(vehicle.signorm[,1])
par(op)

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found