Adding keyword break ties to SVC
@@ -412,7 +412,7 @@ def fit(self, X, y, sample_weight=None):
# see comment on the other call to np.iinfo in this file
seed = rnd.randint(np.iinfo('i').max)
- if ( not sparse and not self.probability and
+ if ( not sparse and not self.probability and not self.break_ties and
sample_weight.size == 0 and self.class_weight is None and kernel in ['linear', 'rbf']):
self._daal_fit = True
@@ -513,14 +513,14 @@ class SVC(sklearn.svm.base.BaseSVC):
coef0=0.0, shrinking=True, probability=False,
tol=1e-3, cache_size=200, class_weight=None,
verbose=False, max_iter=-1, decision_function_shape='ovr',
- random_state=None):
+ break_ties=False, random_state=None):
super(SVC, self).__init__(
kernel=kernel, degree=degree, gamma=gamma,
coef0=coef0, tol=tol, C=C, nu=0., shrinking=shrinking,
probability=probability, cache_size=cache_size,
class_weight=class_weight, verbose=verbose, max_iter=max_iter,
- decision_function_shape=decision_function_shape,
+ decision_function_shape=decision_function_shape, break_ties=break_ties,
random_state=random_state)
