Quote:
Originally Posted by jcmorales1564
I think that I am mainly confused with the learning objective of the algorithm in examples 2.2, i.e., what exactly is the machine trying to learn?

Let's pose this in terms of the coins example. If you are trying to distinguish nickels from pennies, but you represent each coin with only one variable (say the size), positive rays would be a model that tries to learn the 'threshold' size above which you classify the coin as a nickel. Now, let's say you are trying to distinguish nickels from all other coins, and you again represent the coin with just its size. The positive interval model tries to learn the range (lower and upper limit) where you would classify the coin as a nickel as opposed to anything else.