Machine Learning in Action

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 ...