I want to make a little project and I want to use neural networks with python. I found that pybrain is the best solution. But until now, all the examples and questions I have found, cannot help me.

I have a sequence of numbers. Hundreds of rows. Some values are missing and instead of a number, there is an "x".

For example

1425234838636**x**40543485435097**x**43953458345345430843967067045764607457607645067045**x**04376037654067458674506704567408576405

and so on. This is just an example. Not my sequence.

I thought to read one by one the values and train my neural net and when I find one 'x' I will predict the number and I will continue training it with the following numbers.

What I have found until now are training like this one

trainSet.addSample([0,0,0,0],[1])

with some inputs and some outputs.

Any advice on how can I continue with it?

Edit: I figure something and I would like to receive feedback because I don't know if it is right.

I still have the string for above. I split it in a list so I have a list where each entity is a number.

for ind in range(len(myList)):

if not myList[ind] == "x" and not myList[ind+1]=="x":

ds.addSample(myList[ind],myList[ind+1])

else:

break

net = FeedForwardNetwork()

inp = LinearLayer(1)

h1 = SigmoidLayer(1)

outp = LinearLayer(1)

net.addOutputModule(outp)

net.addInputModule(inp)

net.addModule(h1)

net.addConnection(FullConnection(inp, h1))

net.addConnection(FullConnection(h1, outp))

net.sortModules()

trainer = BackpropTrainer(net, ds)

trainer.trainOnDataset(ds,1000)

trainer.testOnData(verbose=True)

lis[ind+1] = net.activate((ind,))

GO to the beginning and continue from the last "x" which replaced from the net.activate()

What do you think? Do you believe that something like this will work?