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. In Python's scikit-learn package, the random forest algorithm is implemented in the ensemble module and you can import the random forest class using the following code:

from sklearn.ensemble import RandomForestClassifier

You can create a random forest classifier using the following code:

rf_model = RandomForestClassifier()

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