(self, data_instances, validate_data=None)
Train lr model of role host
        Parameters
        ----------
        data_instances: Table of Instance, input data
Train lr model of role host
        Parameters
        ----------
        data_instances: Table of Instance, input data
Train lr model of role host Parameters ---------- data_instances : Table of Instance input data
def fit(self, data_instances, validate_data=None):
        """
        Train lr model of role host
        Parameters
        ----------
        data_instances: Table of Instance, input data
        """

        LOGGER.info("Enter hetero_logistic_regression host")
        self.header = self.get_header(data_instances)

        classes = self.one_vs_rest_obj.get_data_classes(data_instances)

        if len(classes) > 2:
            self.need_one_vs_rest = True
            self.need_call_back_loss = False
            self.one_vs_rest_fit(train_data=data_instances, validate_data=validate_data)
        else:
            self.need_one_vs_rest = False
            self.fit_binary(data_instances, validate_data)
def fit ( self , data_instances , validate_data = None ) : LOGGER . info ( "Enter hetero_logistic_regression host" ) self . header = self . get_header ( data_instances ) classes = self . one_vs_rest_obj . get_data_classes ( data_instances ) if len ( classes ) > 2 : self . need_one_vs_rest = True self . need_call_back_loss = False self . one_vs_rest_fit ( train_data = data_instances , validate_data = validate_data ) else : self . need_one_vs_rest = False self . fit_binary ( data_instances , validate_data )