mmnorm {dprep} | R Documentation

## Min-max normalization

### Description

This is a function to apply min-max normalization to a matrix or dataframe.

### Usage

    mmnorm(data,minval=0,maxval=1)

### Arguments

`data` | the dataset to be normalized, including classes
`minval` |
`maxval` |

{the maximum value of the transformed range}

### Details

Min-max normalization subtracts the minimum value of an attribute from each value of the attribute and then divides the difference by the range of the attribute. These new values are multiplied by the new range of the attribute and finally added to the new minimum value of the attribute. These operations transform the data into a new range, generally [0,1].

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

### Value

`zdata3` | the original dataset normalized by min-max normalization.

### Author(s)

Caroline Rodriguez and Edgar Acuna

### References

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

### Examples

    #---- Min-Max Normalization----
    data(ionosphere)
    ionos.minmax=mmnorm(ionosphere)
    op=par(mfrow=c(2,1))
    plot(ionosphere[,1])
    plot(ionos.minmax[,1])
    par(op)

[Package dprep version 1.0 Index]