title: Specific query regarding terminology used in relation to kernel function and support vector machines
body: <p>I am currently reading the book "An Introduction to Support Vector Machines and Other Kernel Based Methods" by Nello Cristianini and I am unable to wrap my head around the concept of dual representation of linear learning machines that he discusses in chapter 2 and later also in chapter 3 in section 3.2, "The Implicit Mapping Into Feature Space", I am unaware of whether this dual representation is a general concept or whether it is a naming convention specific to this book. So that is why I am specifically citing the book and the section if anyone has already read it. If it is a general concept however I would appreciate if anyone could clarify what dual representation of a linear learning machine means and what the advantages of this dual representation are? </p>
  
  <p>I hope this is not too vague a question, but unfortunately I do not have the background or the understanding of these concepts to expound further on my query.</p>
  
  <p>Any help would be greatly appreciated.</p>