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- W4313288803 abstract "The stock market is an important part of the financial market and is closely related to the market development and economic dynamics of the whole country. Due to the volatility of the stock market, such as non-linearity and frequent changes, the accurate prediction of the stock market is usually considered as one of the most challenging problems. In this paper, we propose a stock market prediction model based on the Random Forest algorithm, using historical trading data of several stocks and two ETF funds in the SSE A-share as the research object, and combining AI technology, exemplified by machine learning methods, with the financial industry to predict and analyze stock prices through the model of regression prediction, and the results show that the accuracy of stock prediction using Random Forest is desirable and valuable for guiding institutional and individual stock investments." @default.
- W4313288803 created "2023-01-06" @default.
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- W4313288803 date "2022-10-28" @default.
- W4313288803 modified "2023-09-25" @default.
- W4313288803 title "Research on stock forecasting based on random forest" @default.
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- W4313288803 doi "https://doi.org/10.1109/icdsca56264.2022.9987903" @default.
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