def __init__(self, kernel='rbf'): # Toggle settings here # Best C values for each kernels so far: c_map = {'rbf': 1, 'linear': 0.93939999, 'poly': .012118081} #c_map = {'rbf':1, 'linear':1, 'poly':1} try: SVC.__init__( self, C=c_map[kernel], kernel=kernel, gamma='auto', coef0=0.0, probability=True, shrinking=True, tol=1e-3, cache_size=200, class_weight=None, verbose=False, max_iter=-1, decision_function_shape='ovr', random_state=None, ) except KeyError: print('False kernel') self.name = 'SVM-{:s}'.format(kernel)
def __init__(self, C=1.0, kernel='rbf', degree=3, gamma='auto', coef0=0.0, shrinking=True, probability=True, tol=1e-3, cache_size=200, class_weight=None, verbose=False, max_iter=-1, decision_function_shape='ovr', random_state=None): _SVC.__init__( self, C, kernel, degree, gamma, coef0, shrinking, probability, tol, cache_size, class_weight, verbose, max_iter, decision_function_shape, random_state) BaseWrapperClf.__init__(self)
def __init__(self, **kargs): SVC.__init__(self, **kargs) self.trainX = [] self.trainY = [] self.names = [] self.model = None self.player = SoundPlayer() self.load_mem()
def __init__(self): """ constructor """ SVC.__init__(self, C=1e10, kernel='linear')
def __init__(self, pmml): PMMLBaseClassifier.__init__(self, pmml) OneHotEncodingMixin.__init__(self) SVC.__init__(self) PMMLBaseSVM.__init__(self)
def __init__(self,threshold=1,ll_ranking=False,**kwargs): SV.__init__(self,**kwargs) BaseClassifier.__init__(self,threshold=threshold,ll_ranking=ll_ranking)