To get to clarification of generalizing and overfitting I first must state the following: We have a robot, it makes guesses, and the way we know what guesses to keep is by if the received sensory input matches pre-installed senses that keep it alive/producing. The analog to my terms are training/test data and guessing and ?, correct? So now, it ends up saving better actions to pick up food, then a fork, if the actions are in their teen-age stage then they generalize and can pick up both food and a fork whereas if they are overfit then it only picks up a fork with too much precision. Is that what generalizing and overfit mean?
Clarification of Generalizing and Overfitting
machine learning