TY  - CHAP
AU  - Haixian Wang
ED  - Yagang Zhang
Y1  - 2010-02-01
PY  - 2010
T1  - From Feature Space to Primal Space: KPCA and Its Mixture Model
N2  - The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks, as we use the word in daily life. It is also broad enough to encompass computers that improve from experience in quite straightforward ways. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners. The wide scope of the book provides a good introduction to many approaches of machine learning, and it is also the source of useful bibliographical information.
BT  - New Advances in Machine Learning
SP  - Ch. 7
UR  - https://doi.org/10.5772/9380
DO  - 10.5772/9380
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-18
ER  -