Support Vector Machines pdf epub mobi txt 電子書 下載 2024


Support Vector Machines

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Ingo Steinwart
Springer
2008
601
USD 179.00
Hardcover
9780387772417

圖書標籤: 機器學習  SVM  計算機科學  計算機  計算  數學  Vector  Theory   


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发表于2024-11-10

Support Vector Machines epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Support Vector Machines epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Support Vector Machines pdf epub mobi txt 電子書 下載 2024



圖書描述

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.

The book provides a unique in-depth treatment of both fundamental and recent material on SVMs that so far has been scattered in the literature. The book can thus serve as both a basis for graduate courses and an introduction for statisticians, mathematicians, and computer scientists. It further provides a valuable reference for researchers working in the field.

The book covers all important topics concerning support vector machines such as: loss functions and their role in the learning process; reproducing kernel Hilbert spaces and their properties; a thorough statistical analysis that uses both traditional uniform bounds and more advanced localized techniques based on Rademacher averages and Talagrand's inequality; a detailed treatment of classification and regression; a detailed robustness analysis; and a description of some of the most recent implementation techniques. To make the book self-contained, an extensive appendix is added which provides the reader with the necessary background from statistics, probability theory, functional analysis, convex analysis, and topology.

Support Vector Machines 下載 mobi epub pdf txt 電子書

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Support Vector Machines pdf epub mobi txt 電子書 下載
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