title: is logistic regression large margin classifier?
body: <p>As I understand large margin effect in SVM:</p>
  <p>For example let's look at this image:</p>
  <p><img src="https://i.stack.imgur.com/amyX2.png" alt="SVM" /></p>
  <p>In SVM optimization objective by regularization term we trying to find a set of parameters, where the norm of (parameters vector) theta is small. So we must find vector theta which is small and projections of positive examples (p) on this vector large (to compensate small Theta vector for inner product). In the same time large p gives us <b>large margin</b>. In this image we find ideal theta, and big p with it (and large margin):</p>
  <p><img src="https://i.stack.imgur.com/zRafg.png" alt="SVM2" /></p>
  <h1>My question:</h1>
  <p>Why logistic regression is not large margin classifier? In LR we minimize Theta vector in regularization term in the same way.
  Maybe I did not understand something, if so - correct me.</p>
  <p>I've used images and theory from Coursera ml class.</p>