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)
