def __init__(self,
                 uniform_variables,
                 target_efficiency=0.5,
                 n_neighbors=50,
                 bagging=True,
                 base_estimator=DecisionTreeClassifier(max_depth=1),
                 n_estimators=50,
                 learning_rate=1.,
                 uniforming_rate=1.,
                 train_variables=None,
                 smoothing=0.0,
                 keep_debug_info=False,
                 random_state=None,
                 uniform_label=1,
                 algorithm="SAMME"):

        self.base_estimator = base_estimator
        self.n_estimators = n_estimators
        self.learning_rate = learning_rate
        self.uniforming_rate = uniforming_rate
        self.uniform_variables = uniform_variables
        self.target_efficiency = target_efficiency
        self.n_neighbors = n_neighbors
        self.bagging = bagging
        self.train_variables = train_variables
        self.smoothing = smoothing
        self.uniform_label = uniform_label
        self.keep_debug_info = keep_debug_info
        self.random_state = random_state
        self.algorithm = algorithm
uBoostBDT is AdaBoostClassifier, which is modified to have flat
dataset/ETHPy150Open anaderi/lhcb_trigger_ml/hep_ml/uboost.py/uBoostBDT.__init__