TensorFlow Machine Learning Cookbook - Second Edition

How it works...

Intuitively, we can think of SVM regression as a function that is trying to fit as many points in the  width margin from the line as possible. The fitting of this line is somewhat sensitive to this parameter. If we choose too small an epsilon, the algorithm will not be able to fit many points in the margin. If we choose too large an epsilon, there will be many lines that are able to fit all the data points in the margin. We prefer a smaller epsilon, since nearer points to the margin contribute less loss than further-away points.