# SoftMax: Normalize a set of continuous values using SoftMax In DMwR: Functions and data for "Data Mining with R"

## Description

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

## Usage

 `1` ```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 [email protected]

## References

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

Torgo, L. (2010) Data Mining using R: learning with case studies, CRC Press (ISBN: 9781439810187).

`scale`, `LinearScaling`, `ReScaling`

## Examples

 ```1 2 3``` ```## A simple example with the algae data set summary(SoftMax(algae[,'NO3'])) summary(algae[,'NO3']) ```

### Example output

```Loading required package: lattice