Decision Tree Learning is one of the most widely used and practical methods for inductive inference. Decision tree learning is one of the most successful techniques for supervised classification learning.
Decision Tree Learning Algorithms:
When to use Decision Tree Learning:
- Instances are represented by attribute-value pairs
- The Target function has discrete output values
- Disjunctive descriptions may be required
- The training data may contain errors
- The training data may contain missing attribute values