Split into train and test
Now that we have a dataframe, we can apply standard techniques for modeling. In this exercise, you will split the data into training and test sets.
This exercise is part of the course
Predictive Analytics using Networked Data in R
Exercise instructions
- To ensure the reproducibility of your results, set a seed to 7, using
set.seed(). - Use the
sample()function to sample two-thirds of the numbers from the sequence from the range of the total number of rows instudentnetworkdata. Name this vectorindex_train. - Create the training set by including the rows of
studentnetworkdatathat are stored inindex_trainand name ittraining_set. - Create the test set by excluding the rows of
studentnetworkdatathat are stored inindex_trainand name ittest_set.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Set the seed
set.seed(___)
# Creat the index vector
index_train <- sample(1:nrow(___), 2 / 3 * nrow(___))
# Make the training set
training_set <- ___[index_train,]
# Make the test set
___ <- ___[-index_train,]