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Economic Trend Index Forecasting Using Multiple Regression Model and Random Forest
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- SASAKI Hideaki
- Meiji University
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- URANO Shoichi
- Meiji University
Bibliographic Information
- Other Title
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- 重回帰モデルとランダムフォレストを用いた景気動向指数予測
Description
<p>In this paper, we propose a prediction model that combines statistical methods with different prediction characteristics and machine learning methods in parallel. As a combining method, a multiple regression model and a random forest are used. Because using one method is considered as a risk, the risk is reduced by combining methods with different prediction characteristics. Furthermore, we select effective explanatory variables for economic trend index prediction and improve learning to improve prediction accuracy.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2020 (0), 2I1GS202-2I1GS202, 2020
The Japanese Society for Artificial Intelligence
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Keywords
Details 詳細情報について
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- CRID
- 1390848250119441024
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- NII Article ID
- 130007856907
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- ISSN
- 27587347
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed