O'Reilly logo

Predictive Analytics Using Rattle and Qlik Sense by Ferran Garcia Pagans

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Decision Tree Learning

Decision Tree Learning uses past observations to learn how to classify them and also try to predict the class of a new observation. For example, in a bank, we may have historical information on the granting of loans. Usually, past loan information includes a customer profile and whether the customer defaulted or not. Based on this information, the algorithm can learn to predict whether a new customer will default.

We usually represent a Decision Tree as we did in the following diagram. The root node is at the top, and the leaves of the tree are at the bottom, the leaves represent a decision. In order to create rules from a tree, we need to start from the root node, and then we work downwards, towards the leaves. The following ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required