Metadata-Version: 1.0
Name: liquidSVM
Version: 1.0.1
Summary: Support vector machines (SVMs) and related kernel-based learning
    algorithms are a well-known class of machine learning algorithms, for non-
    parametric classification and regression. liquidSVM is an implementation of
    SVMs whose key features are: fully integrated hyper-parameter selection, extreme
    speed on both small and large data sets, inclusion of a variety of different
    classification and regression scenarios, and full flexibility for experts.
Home-page: http://www.isa.uni-stuttgart.de/software/
Author: Ingo Steinwart, Philipp Thomann
Author-email: philipp.thomann@mathematik.uni-stuttgart.de
License: AGPL v3
Description: liquidSVM for Python
        ====================
        
        Welcome to the Python bindings for liquidSVM.
        
        Summary:
        
        -  Install it using any of the following variants:
        
           ::
        
               pip install --user --upgrade liquidSVM
               easy_install --user --upgrade liquidSVM
        
        -  If you want to compile liquidSVM for your machine download
           http://www.isa.uni-stuttgart.de/software/python/liquidSVM-python.tar.gz.
           For Windows there are binaries at
           `liquidSVM-python.win-amd64.zip <http://www.isa.uni-stuttgart.de/software/python/liquidSVM-python.win-amd64.zip>`__,
           for Mac at
           `liquidSVM-python.macosx.tar.gz <http://www.isa.uni-stuttgart.de/software/python/liquidSVM-python.macosx.tar.gz>`__
        
        Then to try it out issue on the command line
        
        ::
        
            python -m liquidSVM covtype.1000 mc --display=1
        
            **NOTE**: it might be possible that there is a problem with the last
            line if there are files called ``liquidSVM*`` in the current
            directory, so change to some other or a newly created one.
        
        Or use it in an interactive shell
        
        .. code:: python
        
            from liquidSVM import *
            model = mcSVM(iris, iris_labs, display=1,threads=2)
            result, err = model.test(iris, iris_labs)
            result = model.predict(iris)
        
            reg = LiquidData('reg-1d')
            model = lsSVM(reg.test, display=1)
            result.err = model.test(reg.test)
        
        More Information can be found in the
        `demo <http://www.isa.uni-stuttgart.de/software/python/demo.html>`__
        `[jupyter
        notebook] <http://www.isa.uni-stuttgart.de/software/python/demo.ipynb>`__
        and in
        
        .. code:: python
        
            from liquidSVM import *
            help(SVM)
            help(doc.configuration)
        
        Both liquidSVM and these bindings are provided under the AGPL 3.0
        license.
        
        Native Library Compilation
        --------------------------
        
        liquidSVM is implemented in C++ therefore a native library needs to be
        compiled and included in the Python process. Binaries for Windows are
        included, however if it is possible for you, we recommend you compile it
        for every machine to get full performance.
        
        To set compiler options use the the environment variable
        ``LIQUIDSVM_CONFIGURE_ARGS``. The first word in it can be any of the
        following:
        
        ``native``
            usually the fastest, but the resulting library is usually not
            portable to other machines.
        ``generic``
            should be portable to most machines, yet slower (factor 2 to 4?)
        ``debug``
            compiles with debugging activated (can be debugged e.g. with gdb)
        ``empty``
            No special compilation options activated.
        
        The remainder of the environment variable will be passed to the
        compiler. Extract
        http://www.isa.uni-stuttgart.de/software/python/liquidSVM-python.tar.gz
        and change into the directory. On Linux and MacOS X command line use for
        instance:
        
        ::
        
            LIQUIDSVM_CONFIGURE_ARGS="native -mavx2" python setup.py bdist
            LIQUIDSVM_CONFIGURE_ARGS=generic python setup.py bdist
        
        *MacOS*:
            Install Xcode and then the optional command line tools are installed
            from therein.
        
        *Windows*:
            If you have VisualStudio installed then you should have an
            environment variable like ``%VS90COMNTOOLS%`` (for VisualStudio
            2015). Still it seems that setup.py needs to have this information
            in ``%VS90COMNTOOLS%`` so copy that environment variable or use for
            example:
        
            ::
        
                set VS90COMNTOOLS=%VS140COMNTOOLS%
        
                **Note:** At the moment the Visual Studio for Python only gives
                Version 9.0 and this is too old for compilation.
        
        
        
Platform: UNKNOWN
