diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py index d0b8c8b83b589313ebc15d21fa7172200a10433c..2a90d02444feb7ca9bb37144bad30457cf060e1d 100644 --- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py +++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py @@ -15,7 +15,7 @@ from ... import Metrics class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost): def __init__(self, n_max_iterations=None, estimators_generator=None, - random_state=42, self_complemented=True, twice_the_same=False, c_bound_choice = True, random_start = True, divided_ponderation=True, n_stumps_per_attribute=None, use_r=True, plotted_metric=Metrics.zero_one_loss): + random_state=42, self_complemented=True, twice_the_same=False, c_bound_choice = True, random_start = True, n_stumps_per_attribute=None, use_r=True, plotted_metric=Metrics.zero_one_loss): super(ColumnGenerationClassifierQar, self).__init__() self.train_time = 0 @@ -29,14 +29,13 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost): self.twice_the_same = twice_the_same self.c_bound_choice = c_bound_choice self.random_start = random_start - self.divided_ponderation = divided_ponderation self.plotted_metric = plotted_metric if n_stumps_per_attribute: self.n_stumps = n_stumps_per_attribute self.use_r = use_r self.printed_args_name_list = ["n_max_iterations", "self_complemented", "twice_the_same", "c_bound_choice", "random_start", - "divided_ponderation", "n_stumps", "use_r"] + "n_stumps", "use_r"] def set_params(self, **params): self.self_complemented = params["self_complemented"] @@ -132,16 +131,10 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost): self.break_cause = " epsilon was too small." break - if self.divided_ponderation: - if self.use_r: - self.q = (1 / (self.n_max_iterations - k)) * 0.5*math.log((1+r)/(1-r)) - else: - self.q = (1/(self.n_max_iterations-k))*math.log((1 - epsilon) / epsilon) + if self.use_r: + self.q = 0.5*math.log((1+r)/(1-r)) else: - if self.use_r: - self.q = 0.5*math.log((1+r)/(1-r)) - else: - self.q = math.log((1 - epsilon) / epsilon) + self.q = math.log((1 - epsilon) / epsilon) self.weights_.append(self.q) # Update the distribution on the examples. diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py index 08ea973962517dc113ebd6b521144e54c43a0971..97197e805170d605992bd0c68e8e0fcfb8acdd9e 100644 --- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py +++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py @@ -12,7 +12,6 @@ class QarBoostNC(ColumnGenerationClassifierQar, BaseMonoviewClassifier): twice_the_same=False, c_bound_choice=True, random_start=False, - divided_ponderation=False, n_stumps_per_attribute=1, use_r=True )