problem understanding data input setup

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problem understanding data input setup

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I have used weka in the past - various classifiers - all programmed in java
- and all working satifactory :)

I am now delving into deep learning LSTM etc.

I wish to construct a recurrent neural network where

1) input instances are records consisting of 5 fields
a time stamp field
3 forex prices
and the final field is the classifier field (0, 1, 2) [representing "Up",
Down" and "No trade"]

My problem: I wish the input to the neural network to be a multiple number
of instances (say 20)
i.e. the network reads 20 consecutive instances and outputs 1 classification
(0, 1 or 2) [representing the trend of the next 20 instances]
i.e. the training is to be conducted on 20 instances each time - produce a
classification - and repeat by moving the window 1 instance forward, so 20
instances again for training consisting of 19 previous instances and 1 new

Can this be handled and if so, how does one code this in java?

I understand that one could construct each instance with 20 sets of inputs and a classification field but I am hoping one can leave the instances with just the 5 fields as outlined above

Bob M

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