About:
The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.
Changes:
This release contains several enhancements, cleanups and bugfixes:
Features
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Experimental lp-norm MCMKL
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New Kernels: SpectrumRBFKernelRBF, SpectrumMismatchRBFKernel, WeightedDegreeRBFKernel
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WDK kernel supports amino acids
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String Features now support append operations
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python-dbg support
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Allow floats as input for custom kernel (and matrices > 4GB in size)
Bugfixes
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Static linking fix.
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Fix sparse linear kernel's add_to_normal
Cleanup and API Changes
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Remove init() function in Performance Measures
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Adjust .so suffix for python and use python distutils to figure out install paths
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- Operating System:
Cygwin,
Linux,
Macosx
- Data Formats:
Plain Ascii,
Svmlight,
Binary,
Fasta,
Fastq,
Hdf
- JMLR-MLOSS Publication:
JMLR Page
- Tags:
Bioinformatics,
Large Scale,
String Kernel,
Kernel,
Kernelmachine,
Lda,
Lpm,
Matlab,
Mkl,
Octave,
Python,
R,
Svm,
Sgd,
Icml2010,
Liblinear,
Libsvm,
Multiple Kernel Learning,
Ocas
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