Cost Function, Non Convex Optimization, Logistic Regression, Log Loss Function.
1, and we’re only concerned the case that Y equals 1 here. But if H of X is equal to 1. Then the cost is down here is equal to 0. And that is what we like it to be. Because, you know, if we correctly predict the output Y then the cost is 0. But now, notice that H of X approaches 0. So, that’s H. As