This chapter will focus on:
- Decision trees
- How to create decision trees for your application
- Understanding truth tables
- Visual intuition regarding false negatives and false positives
Before we dive right in, let's gain some background information which will be helpful to us.
For a decision tree to be complete and effective, it must contain all possibilities, meaning every pathway in and out. Event sequences must also be supplied and be mutually exclusive, meaning if one event happens, the other one cannot.
Decision trees are a form of supervised machine learning, in that we have to explain what the input and output should be. There are decision nodes and leaves. The leaves are the decisions, ...