def __init__(self):
super(HeteroLRArbiter, self).__init__()
self.gradient_loss_operator = hetero_lr_gradient_and_loss.Arbiter()
self.model_param = HeteroLogisticParam()
self.n_iter_ = 0
self.header = None
self.is_converged = False
self.model_param_name = 'HeteroLogisticRegressionParam'
self.model_meta_name = 'HeteroLogisticRegressionMeta'
self.need_one_vs_rest = None
self.in_one_vs_rest = False
self.mode = consts.HETERO
def __init__(self):
super().__init__()
self.model_name = 'HeteroLogisticRegression'
self.model_param_name = 'HeteroLogisticRegressionParam'
self.model_meta_name = 'HeteroLogisticRegressionMeta'
self.mode = consts.HETERO
self.aggregator = None
self.cipher = None
self.batch_generator = None
self.gradient_loss_operator = None
self.converge_procedure = None
self.model_param = HeteroLogisticParam()
def __init__(self):
super(HeteroLRArbiter, self).__init__()
self.gradient_loss_operator = hetero_lr_gradient_and_loss.Arbiter()
self.model_param = HeteroLogisticParam()
self.n_iter_ = 0
self.header = []
self.is_converged = False
self.model_param_name = 'HeteroLogisticRegressionParam'
self.model_meta_name = 'HeteroLogisticRegressionMeta'
self.model_name = 'HeteroLogisticRegression'
self.need_one_vs_rest = None
self.need_call_back_loss = True
self.mode = consts.HETERO
self.transfer_variable = HeteroLRTransferVariable()