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Diffstat (limited to 'sci-libs/shogun/metadata.xml')
| -rw-r--r-- | sci-libs/shogun/metadata.xml | 32 |
1 files changed, 0 insertions, 32 deletions
diff --git a/sci-libs/shogun/metadata.xml b/sci-libs/shogun/metadata.xml deleted file mode 100644 index 88454ce87eb6..000000000000 --- a/sci-libs/shogun/metadata.xml +++ /dev/null @@ -1,32 +0,0 @@ -<?xml version="1.0" encoding="UTF-8"?> -<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd"> -<pkgmetadata> - <maintainer type="project"> - <email>sci@gentoo.org</email> - <name>Gentoo Science Project</name> - </maintainer> - <longdescription lang="en"> - SHOGUN - is a new machine learning toolbox with focus on large - scale kernel methods and especially on Support Vector Machines - (SVM) with focus to bioinformatics. It provides a generic SVM - object interfacing to several different SVM implementations. Each - of the SVMs can be combined with a variety of the many kernels - implemented. It can deal with weighted linear combination of a - number of sub-kernels, each of which not necessarily working on the - same domain, where an optimal sub-kernel weighting can be learned - using Multiple Kernel Learning. Apart from SVM 2-class - classification and regression problems, a number of linear methods - like Linear Discriminant Analysis (LDA), Linear Programming Machine - (LPM), (Kernel) Perceptrons and also algorithms to train hidden - markov models are implemented. 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. - </longdescription> - <use> - <flag name="R">Enable support for <pkg>dev-lang/R</pkg></flag> - <flag name="octave">Enable support for <pkg>sci-mathematics/octave</pkg></flag> - <flag name="opencl">Enable support for building against OpenCL</flag> - </use> -</pkgmetadata> |