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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods John Shawe-Taylor, Nello Cristianini
Publisher: Cambridge University Press

It is supported on Linux Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. Download free An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini , John Shawe-Taylor B01_0506 John Shawe-Taylor Nello Cristianini pdf chm epub format. The classification can be performed by a large variety of methods, including linear discriminant analysis [5], support vector machines [6], or artificial neural networks [2]. Bpnn.py - Written by Neil Schemenauer, bpnn.py is used by an IBM article entitled "An introduction to neural networks". 515/, An introduction to support Vector Machines: and other kernel-based learning methods, N Cristianini… - 2000 - books.google.com. With these methods In addition to the classification approach, other methods have been developed based on pattern recognition using an estimation approach. Moreover, it analyses the impact of introducing dynamic contractions in the learning process of the classifier. Shogun - The machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM) . For example, the hand dynamic contractions. PyML focuses on SVMs and other kernel methods.