Hands-On Data Science for Marketing

Random forest model

With the data that we have prepared so far, we are going to build a predictive model using a random forest algorithm, which predicts whether a customer is going to respond or engage with the marketing campaign. We are going to use the randomForest R library. If you do not have this library installed in your R environment, you can install it using the following command:

install.packages('randomForest')

Once you have this package installed, you can use the following code to build a random forest model:

library(randomForest)rfModel <- randomForest(x=trainX, y=factor(trainY))

However, there are many hyperparameters you can tune for random forest models. Hyperparameters are the parameters you define before you train a machine ...