Research Article
RLSTM: A New Framework of Stock Prediction by Using Random Noise for Overfitting Prevention
Table 1
The parameters in our experiments.
| Parameters | Value |
| Learning rate | 0.00001 | Number of hidden units in prediction module | 32 | Batch size | 32 | Percentage of training dataset | 70% | Percentage of validation dataset | 10% | Percentage of testing dataset | 20% |
|
|