Support vector machines can be used to fit linear regression. In this chapter, we will explore how to do this with TensorFlow.
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 data set, 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 max . Here, is half of the width of the margin, which makes the loss ...