Product recommendation based on behavior data of the client

Hello everyone

I am fairly new to Knime and we are using it in our classes. I would like to create a model that recommends the next product to the customer. To do this, I have a dataset that contains all the products a customer has bought every month for the last 1.5 years. The goal is to predict the next product he/she will buy.

Which node is best suited for this? Decision Tree, Random Forest, XGBoost or is there another option?

Thanks for the help

Sam