Supervised /
Decision Tree
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The model can only predict based on known samples.
The model learns a hierarchy of if/else questions.
Information gain helps identify attributes with more information.
Pruning allows us to select the most useful attributes.
Can a Decision tree model predict the unknown?
What hierarchy does the model learn?
How is information gain used?
Why do we use pruning?