SVM can be used to fit linear regression. In this section, we will explore how to do this with TensorFlow.
Reduction to linear regression
Getting ready
The same maximum margin concept can be applied toward fitting linear regression. Instead of maximizing the margin that separates the classes, we can think about maximizing the margin that contains the most (x, y) points. To illustrate this, we will use the same iris dataset, and show that we can use this concept to fit a line between sepal length and petal width.
The corresponding loss function will be similar to 
. Here,
is half of the width of the margin, which makes the loss equal to 0 if a point lies in this region.
