NARX Time series Neural Network
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Hi,
I have a cell array that contains 2000 separate time series of data. The arrays in the cells are of different length, ranging from about 1 to 20 days, 1 reading per day. Its 2000 patients with readings taken over a number of days and I am trying to predict one value from this
I think want to make each of the time series the same length so that I can try to do time series prediction which is what this says: href = ""<http://webcache.googleusercontent.com/search?q=cache:bdrNPdyY_i0J:www.mathworks.com/help/toolbox/nnet/ug/bss36ff-1.html+&cd=3&hl=en&ct=clnk</a>>
I have tried to do it using this:
xxx = catsamples(getelements(big,1),'pad')
but I keep getting the error X{1,2} and X{1,1} have different numbers of rows.
which is true, but I thought that using the above would make them the same length and merge them, so that I can feed the 2000 instances in as inputs to a neural network.
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Greg Heath
le 15 Sep 2012
Since your output is one value, it is not a time series problem.
If that value is a classification into 1 of c categories, use patternnet.
Otherwise use fitnet.
Unfortunately, the data for each net has to have the same number of input variable rows. Therefore you can make 20 different data bases... one with 20 inputs, one with 19 inputs(including those with 20 inputs with the last input deleted) etc.
Hope this helps.
Thank you for officially accepting my answer (;>)
Greg
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