def __init__(self, features, trees):
"""
Boosted ODT, which follows REP conventions though cannot be fiited.
:param features: list of strings, features used.
:param trees: list of tuples, each tuple represents a tree.
Tuple is features (features, cuts, leaf_values)
"""
Classifier.__init__(self, features)
self.trees = trees
def __init__(self, features, trees):
"""
Boosted ODT, which follows REP conventions though cannot be fiited.
:param features: list of strings, features used.
:param trees: list of tuples, each tuple represents a tree.
Tuple is features (features, cuts, leaf_values)
"""
Classifier.__init__(self, features)
self.trees = trees
def __init__(self,
base_estimator,
n_folds=2,
random_state=None,
train_features=None,
parallel_profile=None, group_feature=None):
self.group_feature = group_feature
self.train_features = train_features
self.estimators = []
self.parallel_profile = parallel_profile
self.n_folds = n_folds
self.base_estimator = base_estimator
self._folds_indices = None
self.random_state = random_state
self._random_number = None
# setting features directly
Classifier.__init__(self, features=self._features())