Python Deep Learning - Second Edition

Decision Trees

Another popular supervised algorithm is the decision tree. A decision tree creates a classifier in the form of a tree. This is composed of decision nodes, where tests on specific attributes are performed; and leaf nodes, which indicate the value of the target attribute. To classify a new sample, we start at the root of the tree and navigate down the nodes until we reach a leaf.

A classic application of this algorithm is the Iris flower dataset (http://archive.ics.uci.edu/ml/datasets/Iris), which contains data from 50 samples of three types of Irises (Iris Setosa, Iris Virginica, and Iris Versicolor). Ronald Fisher, who created the dataset, measured four different features of these flowers:

• The length of their sepals
• The width ...