New Methods in Data Mining: Support Vector Machines

Author: Deng Naiyang
Publisher:
Publish Date: 2004-06-01
Features: Support Vector Machines (SVM) are a new method in data mining. SVM can very successfully handle a wide range of problems, including regression (time series analysis) and pattern recognition (classification problems, discriminant analysis). It can also be extended to fields such as prediction and comprehensive evaluation, making it applicable to various disciplines like science, engineering, and management. Currently, SVM is experiencing rapid development in both theoretical research and practical applications internationally. It is hoped that this book can promote its popularization and advancement in China. The target audience includes both theoretical researchers and practical workers who are interested in applications. For practical workers with advanced mathematical knowledge in related fields, skipping certain theoretical sections of the book will still allow them to gain a general understanding of the essence of SVM, enabling them to apply it to solve their own problems. This book is suitable for senior undergraduate and graduate students, teachers, and researchers in relevant fields, as well as practical workers in related disciplines.