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.