Closed ron-weiner closed 6 years ago
There are 128 time steps, not 128 features. If you want to change that number, it is on this line of code:
n_steps = len(X_train[0])
Changing the dataset should change the neural net's architecture automatically. However, You may need to make the neural net bigger and change other parameters too.
Thanks for your reply! I meant 3072 time steps. I understood where it is calculated and it didn't raise any error, but I don't think it can run that way in our lifetime.. I couldn't even finish building it.
I wish to use your code on some eeg data, I have 9 channels, 3 output classes and 3072 time steps in my case but I don't think it is necessary to connect between ALL their cells like you have done in your work, I tried to understand how it is possible to focus on shorter amount of time steps, like 300, (like a time window) that will progress until it will reach total time steps.
Any idea how it can be implemented ? Or do you maybe have a better way?
Thank you
LSTM is bad for long time series. It is still about short-term memory, despite it has one longer than an RNN. You may want to check out PLSTMs or use convs+pooling to shorten your signal before an RNN.
thank you very much i will check those!
You have done a great job, applause :)
Hey, Is there a way to handle a big amount of time steps (3072) instead of 128 with minor changes?
Thanks