From the reviews:
„This broad and deep … book is organized around the highly significant concept of pattern recognition by support vector machines (SVMs). … The book is praxis and application oriented but with strong theoretical backing and support. Many … details are presented and discussed, thereby making the SVM both an easy-to-understand learning machine and a more likable data modeling (mining) tool. Shigeo Abe has produced the book that will become the standard … . I like it and therefore highly recommend this book … .“ (Vojislav Kecman, SIAM Review, Vol. 48 (2), 2006)
Support Vector Machines for Pattern Classification
von Shigeo AbeI was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi? ers that we had developed withourbestendeavors. Classi? cationperformanceofourfuzzyclassi? erswas comparable, but in most cases inferior, to that of support vector machines. This tendency was especially evident when the numbers of class data were small. I shifted my research e? orts from developing fuzzy classi? ers with high generalization ability to developing support vector machine–based classi? ers. This book focuses on the application of support vector machines to p- tern classi? cation. Speci? cally, we discuss the properties of support vector machines that are useful for pattern classi? cation applications, several m- ticlass models, and variants of support vector machines. To clarify their - plicability to real-world problems, we compare performance of most models discussed in the book using real-world benchmark data. Readers interested in the theoretical aspect of support vector machines should refer to books such as [109, 215, 256, 257].
