minmaxScaling: The Min-Max Feature Scaling Function
In gradDescent: Gradient Descent for Regression Tasks

Description Usage Arguments Details Value See Also Examples

A function to do feature scaling to dataset with min-max scaling method.

1	minmaxScaling(dataSet)

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).

This function changes the value of dataset that represented by data.frame object into min-max scaled value that has interval between 0 to 1.

a list contains feature scaled dataset and scaling parameter

minmaxDescaling

##################################
## Feature scaling with Min-Max Scaling Method
## load R Package data
data(gradDescentRData)
## get z-factor Data
dataSet <- gradDescentRData$CompressilbilityFactor
## do min-max scaling to dataset
featureScalingResult <- minmaxScaling(dataSet)
## show result
print(featureScalingResult$scaledDataSet)
print(featureScalingResult$scalingParameter)