Code documentation?

[vinhqdang]

Hello

Could you give some explanations of what you did with RNN? It seems to me that it is quite different from RNN implemented in Lua (https://github.com/jcjohnson/torch-rnn): for instance, why do you need to convert everything to binary first?

[bquast]

Hey, its not necessary to convert to binary first, this project grew out of a proof-of-work. The standard RNN problem to train a (3 node) RNN to learn how to carry a 1.

To sum, it was the first application, the functions are still included for the example. Have a look at another example here:

http://shiny.qua.st:3838/

[vinhqdang]

Hi, I think there is a problem with the example (no 'rnn' package). Am I right?

[vinhqdang]

And could I set number of layers in RNN?

[bquast]

I am not sure about no 'rnn' package, do you mean this:

Error in library(rnn) : there is no package called ‘rnn’

If so, you need to install the package, this is explained in the README at the bottom of the page.

[bquast]

Once you have installed the package and loaded it using library(rnn) have a look at the help page using:

help('trainr')

[vinhqdang]

Yes, I saw the parameter _hiddendim, which I think it is the size of RNN, but not sure if it is the number of layers?

[vinhqdang]

We are mixing two discussion threads. For running your example on Shiny, what should I do? I clicked to the center figure and it led me to http://shiny.qua.st:3838/finance/, and there is an error message as you showed.

I installed rnn on my local R and am running with this, but how could I install it on your server? Sorry, I am not very familiar with Shiny.

[bquast]

ah sorry, that must've been the update to R 3.3.0, I reinstalled rnn, checkout the shiny app again.

If you've installed the development (github version) on your system then you can use multiple layers using:

hidden_dim = c(8,5,3)

etc.

[vinhqdang]

Great

It means the RNN will have 3 layers, with the size is 8, 5 and 3 respectively, right?

[bquast]

That's right, it means the first hidden layer is of size 8, the second of size 5 and the third of size 3. Would you mind posting your question on Stackoverflow? That way others can also benefit from this.

[vinhqdang]

Hi,

I submitted a question on StackExchange here:

http://stats.stackexchange.com/questions/218231/understanding-the-example-of-rnn-package-in-r

[vinhqdang]

Hi,

I think this question is still an open one