What is the difference between eager learning and lazy learning?
How does eager learning or lazy learning help me build a neural network system? And how can I use it for any target function?
Artificial Intelligence Stack Exchange is a question and answer site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment. It only takes a minute to sign up.Sign up to join this community
What is eager learning or lazy learning?
Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.
Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Eager learning is also known as instance-based learning [1, 2, 3].
How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?
To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.