ably the most commonly used linear classifier, maybe the most commonly used classifier overall.
The idea is to model the log-odds, which is log p(y=1|x) - log p(y=0|x) as a linear function, as shown here.
Rearranging the formula, you get a model of p(y=1|x) as 1 over 1 + ...
This function is called the logistic sigmoid, and is drawn to the right here. Basically it squashed the linear function $w^Tx$
between 0 and 1, so that it can model a probability.

Given this equation for p(y|x), what we want to do is m