Learning with Kernels 新书_图书内容介绍_剧情呢
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Learning with Kernels读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 648页 9.9 2020 The MIT Press
定价 出版日期 最近访问 访问指数
USD 79.00 2020-02-20 … 2020-03-06 … 59
主题/类型/题材/标签
机器学习,核方法,MachineLearning,Kernels,支持向量机与核方法,kernel,数学,支持向量机,
作者
Bernhard Schlkopf      ISBN:9780262194754    原作名/别名:《》
内容和作者简介
Learning with Kernels摘要

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tas...

作者简介

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

本书后续版本
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