Decision tree learning is a method for approximating definite valued target variables, represented as decision trees or sets of if-then rules for easier understanding. It can be applied in contexts such as diagnosing medical cases and analyzing credit risk for loan applicants. For further information, a link is provided to additional resources.

1. Topic: Decision tree learning

2. Definition
Decision tree learning is a type of learning method
which we apply for approximating definite valued
target variables.
We represent the learned variable with the help of a
decision tree.

3. Another learning method
Decision trees can also be re-represented as
sets of if-then rules to improve human
readability.

4. Examples for the use of decision tree
learning
You may learn to diagnose medical cases by decision
tree learning and learning through sets of if-then rules.
And
If you are an accountant, you can analyse the credit risk
of loan applicants through these methods.

5. For more information:
https://writermahar.blogspot.com/p/the-
decision-tree-learning.html