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  3. Predictive Analytics using Networked Data in R

Exercise

Random forest model

In this exercise, you will use the randomForest() function in the randomForest package to build a random forest model for predicting churn of the customers in the training data set, training_set. The target variable is called Future. You will also inspect and visualize the importance of the variables in the model.

Instructions

100 XP
  • Load the randomForest package.
  • Use the set.seed() function with the seed 863.
  • Build a random forest using the function randomForest() and all the variables in training_set. The response variable Future needs to be a factor, so utilize the as.factor() function.
  • Plot the variable importance of the random forest model using varImpPlot().