def grid_search(self, kernel, labels, C_range=(-15, 15), gamma_range=(-15, 15)):
C_min = C_range[0]
C_max = C_range[1]
params = {'C': [2 ** i for i in range(C_min, C_max, 1)]}
if gamma_range:
gamma_min = gamma_range[0]
gamma_max = gamma_range[1]
params['gamma'] = [2 ** i for i in range(gamma_min, gamma_max, 1)]
data = VectorCreator.make_vectors(self.preprocessor, self.n_chars_extractor, self.pos_tag_extractor)
return ClassifierBase.grid_search(SVC(kernel=kernel), data, labels, params)
def train(self, kernel, params): C = params['C'] gamma = params['gamma'] svc = SVC(C=C, gamma=gamma, kernel=kernel) data = VectorCreator.make_vectors(self.preprocessor, self.n_chars_extractor, self.pos_tag_extractor) ClassifierBase.train(svc, data)