Stock_Prediction_Model_XgBoost.py 文件源码

def do_run(self, train, predict, window):
        LabelColumnName = 'label'
        data_file = "data_file_xgboost_" + str(window) + ".pkl"

        if os.path.exists(data_file):
            input = open(data_file, 'rb')
            data_feature = pickle.load(input)
            input.close()
        else:
            data_feature = get_all_stocks_feature_data(self.paras, window, LabelColumnName)
            output = open(data_file, 'wb')
            pickle.dump(data_feature, output)
            output.close()

        model = None

        train_feature = {}

        if train: model = self.train_data(data_feature, window, LabelColumnName)

        if predict: self.predict_data(model, data_feature, window, LabelColumnName)