Splitting the data into training and testing sets - R

Question

I am working with the 'beaver1' data-set, below is a sample:

   day time  temp activ
1 346  840   36.33   0
2 346  850   36.34   0
3 346  900   36.35   0
4 346  910   36.42   0
5 346  920   36.55   0
6 346  930   36.69   0

I want to split this data into 'train' and 'test' sets with 65:35 ratio so that i can build a machine learning model on top of it, how can i do it?

Answer 1

You can use the sample.split() function from the caTools package for this purpose:

Start off by loading the 'caTools' package:

library(caTools)

Then, use the sample.split() function which takes in two parameters -> the dataset - 'beaver1' and SplitRatio - 0.65

sample.split(beaver1,SplitRatio = 0.65)->mysplit

Following which, use the subset() function and select all those observations where 'mysplit' tag is True and store them in 'train'

subset(beaver1,mysplit==T)->train

Similarly, select all those observations where  the 'mysplilt' tag is Fasle, and store them in 'test'

subset(beaver1,mysplit==F)->test

And that's how you split the data into 'train' and 'test' sets.

Answer 2

Hi,

Try like this.

train  = sample(x = c(TRUE, FALSE), size = nrow(dataframe),replace = TRUE, prob = c(0.65, 0.35))

Get training and test data frame from the main dataset.

data[train,]
data[!train,]