| <?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> |