基于HMM-LSTM隐马尔可夫和长短期记忆模型的股票市场预测
隐马尔可夫模型 (HMM) 是一种信号预测模型，已被用于预测经济状况和股票价格。 该项目旨在实现将机器学习算法应用于股票市场的目标。 长短期记忆模型（LSTM）保证了在新的时间状态下，随着隐藏层不断叠加输入序列，之前的信息可以继续向后传播而不会消失。我们的主要目的是通过预测一只股票的涨跌 使用 HMM-LSTM。
Experiment with 4 different models:
GMM-HMM
XGB-HMM
GMM-HMM-LSTM
XGB-HMM-LSTM
Compared with the results:
train_set
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资源详情
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