27th International Conference on Machine Learning (ICML), Haifa 2010

Shogun

author: Sören Sonnenburg, Machine Learning and Intelligent Data Analysis Group, TU Berlin
published: July 20, 2010, recorded: June 2010, views: 251

Slides

Slides
0:00	The SHOGUN Machine Learning Toolbox
0:23	Outline
0:24	SHOGUN Machine Learning Toolbox - Overview - 1
1:57	SHOGUN Machine Learning Toolbox - Overview - 2
3:45	Feature Representations
7:23	Interfaces
9:17	The Eierlegendewollmilchsau Interface
12:46	Unique Features of SHOGUN - 1
13:48	Unique Features of SHOGUN - 2
14:38	Application
15:18	Demo
16:41	Summary

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Description

The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for kernel machines and features 15 different SVM implementations that all access features in a unified way via a general kernel framework or in case of linear SVMs so called "DotFeatures", i.e., features providing a minimalistic set of operations (like the dot product).