Chapter 6. Support vector machines


This chapter covers
  • Introducing support vector machines
  • Using the SMO algorithm for optimization
  • Using kernels to “transform” data
  • Comparing support vector machines with other classifiers


I’ve seen more than one book follow this pattern when discussing support vector machines (SVMs): “Here’s a little theory. Now SVMs are too hard for you. Just download libsvm and use that.” I’m not going to follow that pattern. I think if you just read a little bit of the theory and then look at production C++ SVM code, you’re going to have trouble understanding it. But if we strip out the production code and the speed improvements, the code becomes manageable, perhaps understandable.

Support vector ...

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