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http://dx.doi.org/10.5392/JKCA.2020.20.12.049

Prediction on the Ratio of Added Value in Industry Using Forecasting Combination based on Machine Learning Method  

Kim, Jeong-Woo (강릉원주대학교 경제학과)
Publication Information
The Journal of the Korea Contents Association / v.20, no.12, 2020 , pp. 49-57 More about this Journal
Abstract
This study predicts the ratio of added value, which represents the competitiveness of export industries in South Korea, using various machine learning techniques. To enhance the accuracy and stability of prediction, forecast combination technique was applied to predicted values of machine learning techniques. In particular, this study improved the efficiency of the prediction process by selecting key variables out of many variables using recursive feature elimination method and applying them to machine learning techniques. As a result, it was found that the predicted value by the forecast combination method was closer to the actual value than the predicted values of the machine learning techniques. In addition, the forecast combination method showed stable prediction results unlike volatile predicted values by machine learning techniques.
Keywords
Machine Learning; Prediction; Forecast Combination; Recursive Feature Elimination;
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