I am new to machine learning and I am confused with the terminology. Thus far, I used to view a hypothesis class as different instance of hypothesis function... Example: If we are talking about linear classification then different lines characterized by different weights would together form the hypothesis class.
Is my understanding correct or can a hypothesis class represent anything which could approximate the target function? For instance, can a linear or quadratic function that approximates the target function together form a single hypothesis class or both are from different hypothesis classes?