Working with a Linear SVM

For this example, we will create a linear separator from the iris data set. We know from prior chapters that the sepal length and petal width create a linear separable binary data set for predicting if a flower is I. setosa or not.

Getting ready

To implement a soft separable SVM in TensorFlow, we will implement the specific loss function, as follows:

Getting ready

Here, A is the vector of partial slopes, b is the intercept, Getting ready is a vector of inputs, is the actual class, (-1 or 1) and is the soft separability regularization parameter.

How to ...

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