An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by John Shawe-Taylor, Nello Cristianini

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods



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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods John Shawe-Taylor, Nello Cristianini ebook
Page: 189
ISBN: 0521780195, 9780521780193
Format: chm
Publisher: Cambridge University Press


Support Vector Machines (SVMs) are a technique for supervised machine learning. It has been shown to produce lower prediction error compared to classifiers based on other methods like artificial neural networks, especially when large numbers of features are considered for sample description. Mathematical methods in statistics. Princeton, NJ: Princeton University Press. Cristianini, N., & Shawe-Taylor, J. Nello Cristianini, John Shawer-Taylor [2] 数据挖掘中的新方法-支持向量机 邓乃扬， 田英杰 [3] 机器学习. Publisher: Cambridge University Press; 1 edition Language: English ISBN: 0521780195 Paperback: 189 pages Data: March 28, 2000 Format: CHM Description: free Download not from rapidshare or mangaupload. Introduction to support vector machines and other kernel-based learning methods. [8] Nello Cristianini and John Shawe-Taylor, “An Introduction to Support Vector Machines and Other Kernel-based Learning Methods”, Cambridge University Press, 2000. [1] An Introduction to Support Vector Machines and other kernel-based learning methods. This is because the only time the maximum margin hyperplane will change is if a new instance is introduced into the training set that is a support vectors.