Decision tree is a technique that helps us in deriving rules from data. A rule-based technique is very helpful in explaining how the model is supposed to work in estimating a dependent variable value.
A typical decision tree looks like this:
The preceding diagram is explained as follows:
- ROOT Node: This represents the entire population or a sample, and it is further divided into two or more further nodes.
- Splitting: A process of dividing a node into two or more subnodes based on a certain rule.
- Decision Node: When a subnode splits into further subnodes, it is called decision node.
- Leaf/Terminal Node: The final node in a decision ...
