What’s the difference between a “training set” and a “test set”?
Why might a pruned decision tree that doesn’t fit the data so well be better than an un-pruned one?
What’s the first thing that 1R does when making a rule based on a numeric attribute?
How does 1R avoid overfitting when making a rule based on an enumerated and/or numeric attribute?
What is the difference between Attribute, Instance and Training set?
What is the difference between ID3 and C4.5?