Ejemplo n.º 1
0
 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
Ejemplo n.º 2
0
 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
Ejemplo n.º 3
0
 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())