In this post we are going to manage a Classification problem, by using some CART models (Classification And Regression Trees).
We will use the following Bank Marketing Data Set dataset, provided by the UCI Machine Learning Repository:
ref. [Moro et al., 2014] S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014
These are the results about some direct marketing campaigns carried out by a Portuguese bank by using outbound contact center calls, to try to sell repo financial products to customers.
The labeled output data we are interested in predicting are “binary” (column y): “yes” in the event that customers have accepted the bank deposit offer or “no” if the offer has been rejected.
Let’s import some useful libraries with scikit-learn:
Continue reading “Random forest”