Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to understand data sampling in R:

1. To generate random samples of a given population, the user can simply use the sample function:

        > sample(1:10)  

2. To specify the number of items returned, the user can set the assigned value to the size argument:

        > sample(1:10, size = 5)  

3. Moreover, the sample can also generate Bernoulli trials by specifying replace = TRUE (default is FALSE):

        > sample(c(0,1), 10, replace = TRUE)  

4. If we want to do a coin flipping trail, where the outcome is Head or Tail, we can use:

          > outcome <- c("Head","Tail")
          > sample(outcome, size=1)  

5. To generate result for 100 times, we can use:

         > sample(outcome, size=100, replace=TRUE)  

6. The sample can be useful when we want to ...