(self, tree_param: DecisionTreeModelParam, valid_feature: dict, epoch_idx: int,
                 tree_idx: int, flow_id: int)
initializing here
initializing here
initializing here
def __init__(self, tree_param: DecisionTreeModelParam, valid_feature: dict, epoch_idx: int,
                 tree_idx: int, flow_id: int):

        super(HomoDecisionTreeArbiter, self).__init__(tree_param)
        self.splitter = Splitter(self.criterion_method, self.criterion_params, self.min_impurity_split,
                                 self.min_sample_split, self.min_leaf_node, self.min_child_weight)

        self.transfer_inst = HomoDecisionTreeTransferVariable()
        """
        initializing here
        """
        self.valid_features = valid_feature

        self.tree_node = []  # start from root node
        self.tree_node_num = 0
        self.cur_layer_node = []

        self.runtime_idx = 0
        self.sitename = consts.ARBITER
        self.epoch_idx = epoch_idx
        self.tree_idx = tree_idx

        # secure aggregator
        self.set_flowid(flow_id)
        self.aggregator = DecisionTreeArbiterAggregator(verbose=False)

        # stored histogram for faster computation {node_id:histogram_bag}
        self.stored_histograms = {}
def __init__ ( self , tree_param : DecisionTreeModelParam , valid_feature : dict , epoch_idx : int , tree_idx : int , flow_id : int ) : super ( HomoDecisionTreeArbiter , self ) . __init__ ( tree_param ) self . splitter = Splitter ( self . criterion_method , self . criterion_params , self . min_impurity_split , self . min_sample_split , self . min_leaf_node , self . min_child_weight ) self . transfer_inst = HomoDecisionTreeTransferVariable ( ) self . valid_features = valid_feature self . tree_node = [ ] # start from root node self . tree_node_num = 0 self . cur_layer_node = [ ] self . runtime_idx = 0 self . sitename = consts . ARBITER self . epoch_idx = epoch_idx self . tree_idx = tree_idx # secure aggregator self . set_flowid ( flow_id ) self . aggregator = DecisionTreeArbiterAggregator ( verbose = False ) # stored histogram for faster computation {node_id:histogram_bag} self . stored_histograms = { }