MachineLearning (version 0.1.4)

sampler: Splitting your dataset in training and testing

Description

A training/test partition are created by sampler function.

Usage

sampler(data, p, seed = NULL)

Arguments

data

the data frame that contains the variables to be separeted.

p

the percentage of the training dataset to be obtained randomly. It can be expressed in either decimal fraction (such as 0.7) or percent (such as 72.12).

seed

a single value, interpreted as an integer, or NULL. The default value is NULL, but for future checks of the model or models generated it is advisable to set a random seed to be able to reproduce it.

Examples

# NOT RUN {
# The best way to demostrate the functionality is test the function
Sampling <- sampler(EGATUR,p=0.7)



# }