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%