基于LSTM神经网络的通用股票预测源代码+模型+数据集

上传者: 2301_76484015 | 上传时间: 2024-06-07 15:00:05 | 文件大小: 4.9MB | 文件类型: ZIP
使用getdata.py下载数据,或者使用自己的数据源,将数据放在stock_daily目录下 使用data_preprocess.py预处理数据,生成pkl文件,放在pkl_handle目录下(可选) 调整train.py和init.py中的参数,先使用predict..py训练模型,生成模型文件,再使用predict.py进行预测,生成预测结果或测试比照图 本项目使用机器学习方法解决了股票市场预测的问题。项目采用开源股票数据中心的上证000001号,中国平安股票(编号SZ_000001),使用更加适合进行长时间序列预测的LSTM(长短期记忆神经网络)进行训练,通过对训练集序列的训练,在测试集上预测开盘价,最终得到准确率为96%的LSTM股票预测模型,较为精准地实现解决了股票市场预测的问题

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