minmaxDescaling: Min-Max Scaling Revert Function

In gradDescent: Gradient Descent for Regression Tasks

Description

A function to revert the value that has been done by min-max scaling method.

Usage

minmaxDescaling(dataSet, minmaxParameter)

Arguments

dataSet	a data.frame that representing dataset (m \times n), where m is the number of instances and n is the number of variables where the last column is the output variable. dataSet must have at least two columns and ten rows of data that contain only numbers (integer or float).
minmaxParameter	a matrix that has value of minmax scaling parameter, such as minimum value and maximum value of data that can be used to restore the original value of dataset. This parameter is exclusively produced by varianceScaling function.

Details

This function changes the value of min-max scaled dataset that produced by varianceScaling function and represented by data.frame object.

Value

a data.frame representing reverted dataset value

See Also

minmaxScaling

Examples

##################################
## Revert Min-Max Scaling
## load R Package data
data(gradDescentRData)
## get z-factor Data
dataSet <- gradDescentRData$CompressilbilityFactor
fsr <- minmaxScaling(dataSet)
rfsr <- minmaxDescaling(fsr$scaledDataSet, fsr$scalingParameter)

gradDescent documentation built on May 2, 2019, 9:42 a.m.