How to have multiple targets in a neural network?

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Shoumy 2014-11-27

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评论： Royi Avital 2017-3-24

Hello,

I have a question, if I had multiple outputs for a pattern recognition neural network (as in I have 3 different targets, one indicates size, one indicates direction, one indicates angles)(and I have 8 features and 86 samples for input), I want to train them at the same time using one neural network instead on training each target one by one, how would I do that? If I use the toolbox it allows the entry of only one target. Is there a simple way to do this? Doesn't matter if it is in code or toolbox.

Thank you. :)

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采纳的回答

Greg Heath 2014-11-29

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在 MATLAB Online 中打开

For N examples of O outputs corresponding to N examples of I inputs

 [I N ] = size(input)
 [O N ] = size(target)

However, patternnet was designed to represent classes using {0,1} unit target vectors. So, unless you have discrete classes, use regression with fitnet.

Hope this helps.

Thank you for formally accepting my answer

Greg

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Greg Heath 2017-2-12

You mean calculate the outputs. The answer is no.

The weights can be configured in many different ways depending on weight initialization. In general, there is no obvious relationship between the 3 target weights and the 2 or 1 target weight... or if 1 or 2 targets are identically zero.

Hope this helps.

Greg

Royi Avital 2017-3-24

I think one should understand that the Net Object is updated according to the data on the configuration phase before the train test using `configure(hNetModel, mX, mT)`.

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