R programming

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?

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