Package python-module-shogun: Information
Binary package: python-module-shogun
Version: 3.2.0-alt1
Architecture: x86_64
Build time: Jun 3, 2014, 08:49 PM in the task #120704
Source package: shogun
Category: Development/Python
Report package bugHome page: http://www.shogun-toolbox.org/
License: GPL v3 or later
Summary: Python interface for SHOGUN
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. This package contains Python interface for SHOGUN.
Maintainer: Eugeny A. Rostovtsev
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