ent of the number of samples as possible in scikit-learn, but that might
lead to surprises if you're not aware of it.

Some side-notes on the optimization problem: here, as in regression, having more regularization
makes the optimization problem easier. You might have seen this in your homework already, if
you decrease C, meaning you add more regularization, your model fits more quickly.

One particular property of the logistic loss, compared to the hinge loss we'll discuss next is that
each data point cont