Suppose that we use a perceptron to detect spam messages. Let's say that each email message is represented by the frequency of occurrence of keywords, and the output is if the message is considered spam.

Can you think of some keywords that will end up with a large positive weight in the perceptron?

How about keywords that will get a negative weight?

What parameter in the perceptron directly affects how many borderline messages end up being classified as spam?