Source Code for Module mvpa.clfs.svm

  1  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- 
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  4  # 
  5  #   See COPYING file distributed along with the PyMVPA package for the 
  6  #   copyright and license terms. 
  7  # 
  8  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## 
  9  """Importer for the available SVM and SVR machines. 
 10   
 11  Multiple external libraries implementing Support Vector Machines 
 12  (Classification) and Regressions are available: LIBSVM, and shogun. 
 13  This module is just a helper to provide default implementation for SVM 
 14  depending on the availability of external libraries. By default LIBSVM 
 15  implementation is choosen by default, but in any case both libraries 
 16  are available through importing from this module: 
 17   
 18  > from mvpa.clfs.svm import sg, libsvm 
 19  > help(sg.SVM) 
 20  > help(libsvm.SVM) 
 21   
 22  Please refer to particular interface for more documentation about 
 23  parametrization and available kernels and implementations. 
 24  """ 
 25   
 26  __docformat__ = 'restructuredtext' 
 27   
 28  # take care of conditional import of external classifiers 
 29  from mvpa.base import warning, cfg, externals 
 30  from _svmbase import _SVM 
 31   
 32  if __debug__: 
 33      from mvpa.base import debug 
 34   
 35  # default SVM implementation 
 36  SVM = None 
 37  _NuSVM = None 
 38   
 39   
 40  # TODO: handle choices within cfg 
 41  _VALID_BACKENDS = ('libsvm', 'shogun', 'sg') 
 42  default_backend = cfg.get('svm', 'backend', default='libsvm').lower() 
 43  if default_backend == 'shogun': 
 44      default_backend = 'sg' 
 45   
 46  if not default_backend in _VALID_BACKENDS: 
 47      raise ValueError, 'Configuration option svm.backend got invalid value %s.' \ 
 48            ' Valid choices are %s' % (default_backend, _VALID_BACKENDS) 
 49   
 50  if __debug__: 
 51      debug('SVM', 'Default SVM backend is %s' % default_backend) 
 52   
 53  if externals.exists('shogun'): 
 54      from mvpa.clfs import sg 
 55      SVM = sg.SVM 
 56      #if not 'LinearCSVMC' in locals(): 
 57      #    from mvpa.clfs.sg.svm import * 
 58   
 59  if externals.exists('libsvm'): 
 60      # By default for now we want simply to import all SVMs from libsvm 
 61      from mvpa.clfs import libsvmc as libsvm 
 62      _NuSVM = libsvm.SVM 
 63      if default_backend == 'libsvm' or SVM is None: 
 64          if __debug__ and default_backend != 'libsvm' and SVM is None: 
 65              debug('SVM', 
 66                    'Default SVM backend %s was not found, so using libsvm' 
 67                    % default_backend) 
 68          SVM = libsvm.SVM 
 69      #from mvpa.clfs.libsvm.svm import * 
 70   
 71  if SVM is None: 
 72      warning("None of SVM implementions libraries was found") 
 73  else: 
 74      _defaultC = _SVM._SVM_PARAMS['C'].default 
 75      _defaultNu = _SVM._SVM_PARAMS['nu'].default 
 76   
 77      # Define some convinience classes 
 78 -    class LinearCSVMC(SVM): 
 79          """C-SVM classifier using linear kernel. 
 80   
 81          See help for %s for more details 
 82          """ % SVM.__class__.__name__ 
 83   
 84 -        def __init__(self, C=_defaultC, **kwargs): 
 85              """ 
 86              """ 
 87              # init base class 
 88              SVM.__init__(self, C=C, kernel_type='linear', **kwargs) 
 89   
 90   
 91 -    class RbfCSVMC(SVM): 
 92          """C-SVM classifier using a radial basis function kernel. 
 93   
 94          See help for %s for more details 
 95          """ % SVM.__class__.__name__ 
 96   
 97 -        def __init__(self, C=_defaultC, **kwargs): 
 98              """ 
 99              """ 
100              # init base class 
101              SVM.__init__(self, C=C, kernel_type='RBF', **kwargs) 
102   
103      if _NuSVM is not None: 
104 -        class LinearNuSVMC(_NuSVM): 
105              """Nu-SVM classifier using linear kernel. 
106   
107              See help for %s for more details 
108              """ % _NuSVM.__class__.__name__ 
109   
110 -            def __init__(self, nu=_defaultNu, **kwargs): 
111                  """ 
112                  """ 
113                  # init base class 
114                  _NuSVM.__init__(self, nu=nu, kernel_type='linear', **kwargs) 
115   
116 -        class RbfNuSVMC(SVM): 
117              """Nu-SVM classifier using a radial basis function kernel. 
118   
119              See help for %s for more details 
120              """ % SVM.__class__.__name__ 
121   
122 -            def __init__(self, nu=_defaultNu, **kwargs): 
123                  # init base class 
124                  SVM.__init__(self, nu=nu, kernel_type='RBF', **kwargs) 
125