The Support Vector Machine can be viewed as a kernel machine. As a result, you can change its behavior by using a different kernel function.

The most popular kernel functions are :

- the linear kernel
- the polynomial kernel
- the RBF (Gaussian) kernel
- the string kernel

## The linear kernel is often recommended for text classification

It is interesting to note that :

The original optimal hyperplane algorithm proposed by Vapnik in 1963 was a linear classifier [1]

That's only 30 years later that the kernel trick was introduced.

If it is the simpler algorithm, **why is the linear kernel recommended for text classification**?

## Text is often linearly separable

Most of text classification problems are linearly separable [2]

Linear kernel works well with linearly separable data

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