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RLSTM: A New Framework of Stock Prediction by Using Random Noise for Overfitting Prevention
An accurate prediction of stock market index is important for investors to reduce financial risk. Although quite a number of deep learning methods have been developed for the stock prediction, some fundamental problems, such as weak generalization ability and overfitting in training, need to be solv...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Hindawi
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8154285/ https://www.ncbi.nlm.nih.gov/pubmed/34113377 http://dx.doi.org/10.1155/2021/8865816 |