Support Vector Machines / Christmann, Andreas
Tác giả : Christmann, Andreas
Nhà xuất bản : Springer
Năm xuất bản : 2008
Mô tả vật lý : 611 p.
Số phân loại : 006.31
Chủ đề : 1. Computer Science. 2. Book.
Thông tin chi tiết
Tóm tắt : | This book explains the principles that make support vector machines (SVMs) a successful modelling and prediction tool for a variety of applications. The authors present the basic ideas of SVMs together with the latest developments and current research questions in a unified style. They identify three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and their computational efficiency compared to several other methods. Since their appearance in the early nineties, support vector machines and related kernel-based methods have been successfully applied in diverse fields of application such as bioinformatics, fraud detection, construction of insurance tariffs, direct marketing, and data and text mining. As a consequence, SVMs now play an important role in statistical machine learning and are used not only by statisticians, mathematicians, and computer scientists, but also by engineers and data analysts. |
Thông tin dữ liệu nguồn
Thư viện | Ký hiệu xếp giá | Dữ liệu nguồn |
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Đại học quốc gia Hà Nội |
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https://repository.vnu.edu.vn/handle/VNU_123/25624 |