Understanding decision trees
As you might intuit from the name, decision tree learners build a model in the form of a tree structure. The model itself comprises a series of logical decisions, similar to a flowchart, with decision nodes that indicate a decision to be made on an attribute. These split into branches that indicate the decision's choices. The tree is terminated by leaf nodes (also known as terminal nodes) that denote the result of following a combination of decisions.
Data that is to be classified begin at the root node where it is passed through the various decisions in the tree according to the values of its features. The path that the data takes funnels each record into a leaf node, which assigns it a predicted class.
As the decision tree is essentially a flowchart, it is particularly appropriate for applications in which the classification mechanism needs to be transparent for legal reasons or the results need to be shared in order to facilitate decision making. Some potential...
