Package: sg
Version: 0.3.2
Date: 2007-01-14
Title: The SHOGUN Machine Learning Toolbox
Author: Soeren Sonnenburg, Gunnar Raetsch, Fabio De Bona
Maintainer: Soeren Sonnenburg <Soeren.Sonnenburg@first.fraunhofer.de>
Depends: R (>= 2.1.0)
Suggests:
Description: The SHOGUN machine learning toolbox's focus is on kernel
        methods and especially on Support Vector Machines (SVM). It
        provides a generic SVM object interfacing to several different
        SVM implementations, among them the state of the art LibSVM[1]
        and SVMlight[2].  Each of the SVMs can be combined with a
        variety of kernels. The toolbox not only provides efficient
        implementations of the most common kernels, like the Linear,
        Polynomial, Gaussian and Sigmoid Kernel but also comes with a
        number of recent string kernels as e.g. the Locality
        Improved[3], Fischer[4], TOP[5], Spectrum[6], Weighted Degree
        Kernel (with shifts)[7]. For the latter the efficient LINADD[8]
        optimizations are implemented.  Also SHOGUN offers the freedom
        of working with custom pre-computed kernels.  One of its key
        features is the ``combined kernel'' which can be constructed by
        a weighted linear combination of a number of sub-kernels, each
        of which not necessarily working on the same domain. An optimal
        sub-kernel weighting can be learned using Multiple Kernel
        Learning[9].  Currently SVM 2-class classification and
        regression problems can be dealt with. However SHOGUN also
        implements a number of linear methods like Linear Discriminant
        Analysis (LDA), Linear Programming Machine (LPM), (Kernel)
        Perceptrons and features algorithms to train hidden markov
        models.  The input feature-objects can be dense, sparse or
        strings and of type int/short/double/char and can be converted
        into different feature types.  Chains of ``preprocessors''
        (e.g. substracting the mean) can be attached to each feature
        object allowing for on-the-fly pre-processing.
License: GPL Version 2 or later.
URL: http://www.r-project.org,
        http://www.fml.tuebingen.mpg.de/raetsch/projects/shogun
Built: R 2.5.0; x86_64-pc-linux-gnu; 2007-06-04 11:52:20; unix
