Question

I have a scenario where my hypothesis fits my training set well but fails to generalize for the test set. What is this scenario called?

Answer 1

This scenario is called over-fitting.

Explanation:

• It happens when a subject learns the information about the training data to the limit that it starts affecting the performance of the subject on new data in a negative way.

• It means that the random changes in the data are taken as concepts by the subject.  

• Now the issue that occurs is that the concepts that are gathered by the subject do not apply to the new information collected and it affects the subject's capability in a negative way.