Package shogun: Information

    Source package: shogun
    Version: 3.2.0-alt1
    Build time:  Jun 3, 2014, 08:49 PM in the task #120704
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    License: GPL v3 or later
    Summary: A Large Scale Machine Learning Toolbox
    Description: 
    The machine learning toolbox's focus is on large scale 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 and SVMlight.  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, Fischer, TOP, Spectrum,
    Weighted Degree Kernel (with shifts). For the latter the efficient
    LINADD 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.
    
    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.

    List of rpms provided by this srpm:
    libshogun (x86_64, i586)
    libshogun-debuginfo (x86_64, i586)
    libshogun-devel (x86_64, i586)
    python-module-shogun (x86_64, i586)
    python-module-shogun-debuginfo (x86_64, i586)
    shogun (x86_64, i586)
    shogun-debuginfo (x86_64, i586)
    shogun-docs (noarch)
    shogun-examples (x86_64, i586)
    shogun-examples-debuginfo (x86_64, i586)
    shogun-tests (noarch)



      1. ghostscript-classic
      2. cmake
      3. graphviz
      4. /proc
      5. doxygen
      6. libnlopt-devel
      7. libnumpy-devel
      8. libglpk36-devel
      9. python-devel
      10. libsuperlu-devel
      11. python-module-docutils
      12. python-module-matplotlib
      13. swig
      14. python-module-wx2.9
      15. texlive-latex-extra
      16. gcc-c++
      17. libarpack-devel
      18. libarprec-devel
      19. libhdf5-devel
      20. libcolpack-devel
      21. libreadline-devel
      22. zlib-devel
      23. libcurl-devel
      24. libxml2-devel
      25. libjson-devel
      26. boost-devel
      27. bzlib-devel
      28. liblzma-devel
      29. liblzo2-devel
      30. ccache
      31. liblapack-devel
      32. libsnappy-devel
      33. liblpsolve-devel

    Last changed


    June 3, 2014 Eugeny A. Rostovtsev 3.2.0-alt1
    - Version 3.2.0
    - Rebuilt with gkpk36
    Jan. 18, 2014 Eugeny A. Rostovtsev 3.0.0-alt2
    - Rebuilt with gkpk35
    Nov. 21, 2013 Eugeny A. Rostovtsev 3.0.0-alt1
    - Version 3.0.0