MATLAB: How to create a target data set based on input data set in a neural network

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I have an input dataset. I want to create a target dataset to perform time series analysis using a neural network. I browsed a lot, but I couldn't find any convincing solution. Can any one help me with this?

Best Answer

If the input data set is x(n), ( n = 1:N )

the output data set could be

 y(n) = f( x(n), x(n-1), ... x(n-m) ), for n > m

Typically, f is linear.

Hope this helps.

Thank you for formally accepting my answer

Greg

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MATLAB: How to train a feedfordward neural network with error weights

 Use the command window
 help mse
 doc mse

Hope this helps.

Thank you for formally accepting my answer

Greg

MATLAB: How to set target vector (with large data set) for neural network

Regardless of data values, use MAPSTD or ZSCORE and training data to normalize inputs.

For c classes, the target matrix should contain columns of the unit matrix eye(c). The relationship between integer class indices 1:c and target vectors are given by functions ind2vec and vec2ind.

You have so much data, you only need a small fraction of it to design a net, or even multiple nets.

Hope this helps.

Thank you for formally accepting my answer

Greg

Best Answer

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MATLAB: How to train a feedfordward neural network with error weights

MATLAB: How to set target vector (with large data set) for neural network

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