LinearScaling: Normalize a set of continuous values using a linear scaling

In DMwR: Functions and data for "Data Mining with R"

Description

Function for normalizing the range of values of a continuous variable using a linear scaling within the range of the variable.

Usage

LinearScaling(x, mx = max(x, na.rm = T), mn = min(x, na.rm = T))

Arguments

x	A vector with numeric values
mx	The maximum value of the continuous variable being normalized (defaults to the maximum of the values in x).
mn	The minimum value of the continuous variable being normalized (defaults to the minimum of the values in x).

Details

The linear scaling normalization consist in transforming the value x into

(x - MIN) / (MAX - MIN)

Value

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

Author(s)

Luis Torgo [e-mail]

References

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

http://www.dcc.fc.up.pt/~ltorgo/DataMiningWithR

See Also

scale, SoftMax, ReScaling

Examples

## A simple example with the algae data set
summary(LinearScaling(algae[,'NO3']))
summary(algae[,'NO3'])

Example output

Loading required package: lattice
Loading required package: grid
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
0.00000 0.02732 0.05757 0.07089 0.09641 1.00000       2 
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.050   1.296   2.675   3.282   4.446  45.650       2 

DMwR documentation built on May 1, 2019, 9:17 p.m.