SoftMax {DMwR2}

Normalize a set of continuous values using SoftMax

Description

Function for normalizing the range of values of a continuous variable using the SoftMax function (Pyle, 199).

Usage

SoftMax(x, lambda = 2, avg = mean(x, na.rm = T), std = sd(x, na.rm = T))

Arguments

x

A vector with numeric values

lambda

A numeric value entering the formula of the soft max function (see Details). Defaults to 2.

avg

The statistic of centrality of the continuous variable being normalized (defaults to the mean of the values in x).

std

The statistic of spread of the continuous variable being normalized (defaults to the standard deviation of the values in x).

Details

The Soft Max normalization consist in transforming the value x into

1 / [ 1+ exp( (x-AVG(x))/(LAMBDA*SD(X)/2*PI) ) ]

Value

An object with the same dimensions as x but with the values normalized

Author(s)

Luis Torgo [e-mail]

References

Pyle, D. (1999). Data preparation for data mining. Morgan Kaufmann.

Torgo, L. (2016) Data Mining using R: learning with case studies, second edition, Chapman & Hall/CRC (ISBN-13: 978-1482234893).

http://ltorgo.github.io/DMwR2

See Also

scale

Examples

## A simple example with the iris data set
data(iris)
summary(SoftMax(iris[["Petal.Length"]]))
summary(iris[["Petal.Length"]])