shogun-elwms 0.10.0-2.1ubuntu1 (amd64 binary) in ubuntu precise
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/
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.
.
SHOGUN comes in different flavours, a stand-a-lone version and also with
interfaces to Matlab(tm), R, Octave, Readline and Python. This is the
eierlegendewol
commands to R, Octave and Python all at once.
Details
- Package version:
- 0.10.0-2.1ubuntu1
- Status:
- Superseded
- Component:
- universe
- Priority:
- Optional
Downloadable files
- shogun-elwms_0.10.0-2.1ubuntu1_amd64.deb (105.8 KiB)
Package relationships
- Depends on:
- libatlas3gf-base
- libc6 (>= 2.2.5)
- libgcc1 (>= 1:4.1.1)
- libpython2.7 (>= 2.7)
- libshogun9 (= 0.10.0-2.1ubuntu1)
- libshogunui6 (= 0.10.0-2.1ubuntu1)
- libstdc++6 (>= 4.1.1)
- octave3.2 (>= 3.2.4)
- python (<< 2.8)
- python (>= 2.7)
- python-numpy (<< 1:1.6)
- python-numpy (>= 1:1.5.1)
- python-support (>= 0.90.0)
- r-base-core