Research on stock price prediction based on lstm model and random forest

HIGHLIGHTS

• What: In this study cutting-edge methods of applying deep learning techniques to stock market predictions were explored specifically focusing on the stock data of Tesla Inc. The innovation of this research lies in the integration of the LSTM model with the Random Forest algorithm forming a hybrid model aimed at leveraging the complementary strengths of both models to improve the accuracy of stock price predictions. This study seeks to investigate the integration of long short-term memory neural_networks (LSTM) and random forest models for feature extraction from market data to forecast price trends.
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