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How can I deal up with manual data division and multiple sequences of time series data?

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Rafael 2012 年 7 月 26 日
コメント済み: Torsten K 2020 年 10 月 20 日
I'm working with Neural Toolbox using a dynamic network with time series data. Data consist on several contiguous data blocks (i.e. multiple sequences). Because there aren't so many large continous blocks, I thought I could make use of 'catsample' function to create a concurrent set of sequences, like described here:
The problem I'm encountering is related to the division of such data. I want to make a manual division into training, validation and testing data sets. So reviewing the data division functions avalaible on neural toolbox I chose the 'divideind' as the most suitable, but time series data are sequential data and therefore it's a cell array of double matrices which in turn each one has a concurrent set of sequences... So I can't imagine how to set up the indices for each data set. Because If I set for example:
[TrainInd, ValInd, TestInd] = divideind(nnInputData, 1:10, 11:20, 21:30);
I get TrainInd with all the sequences and ValInd and TestInd with nothing (just empty [])
Could you tell me some idea please?

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Greg Heath
Greg Heath 2012 年 7 月 26 日
Change your first input
help divideind
doc divideind

  3 件のコメント

Rafael 2012 年 7 月 26 日
Ok, I had misunderstood completely the first arg, I was thinking on it as the data structure :$. Thank you for noticing it.
Then I realize 'divideind' can't be used with multi-sequential data, isn't it? I need something which can differenciate the sequences of data, and not only the time steps.
Greg Heath
Greg Heath 2012 年 7 月 27 日
I think you have to use divideblock so that you
1. Train on 1:Ntrn for multiple candidate values of H (number of hidden nodes) and Ntrials of multiple random weight initializations for each value of H.
2 Choose the best design with the validation data Ntrn+1:Ntrn+Nval
3. Use the test set Ntrn+Nval+1:N to predict performance on unseen data.
Torsten K
Torsten K 2020 年 10 月 20 日
Hello Rafael,
did you find a solution for dividing the complete sequences instead of dividing the time-steps? I would be very interested!
Best regards


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