normalizeData: Normalize Data Set
In mariytu/RegressionLibs: What the package does (short line)

Description Usage Arguments Value See Also Examples

Function to normalize a data set. You could normalize in any range [min,max], but if you don't specify this values, this function make a normalization in range [0,1].

1	normalizeData(dataSet, min, max)

`dataSet`	an object of class data frame with the original data set that you want normalize.
`min`	an integer with the min value that you want normalize the data set.
`max`	an integer with the max value that you want normalize the data set.

an object of class data frame with a modified data set normalized in the defined range.

normalize, scaleData

#Example 1
iris.x <- iris[,1:4] #Just numerical columns witout missing values

normedIris1 <- normalizeData(iris.x) #In range [0,1]
normedIris2 <- normalizeData(iris.x, 1, 10) #In ragen [1,10]


#Example 2
# Getting a data set without missing values
cars <- read.csv("https://dl.dropboxusercontent.com/u/12599702/autosclean.csv", sep = ";", dec = ",")

normedCars1 <- normalizeData(cars) #In range [0,1]
normedCars2 <- normalizeData(cars, 1, 10) #In ragen [1,10]