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 ...

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