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 kernelThe 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 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 separableMost of text classification problems are linearly separable I am passionate about machine learning and Support Vector Machine. I like to explain things simply to share my knowledge with people from around the world. If you wish you can add me to linkedin, I like to connect with my readers.