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If we have neural network and train it with desired outputs such as: if case A the output will be 0.04 if case B then 0.08 if case C then 0.12 and so on until 1

If we got an actual output 0.06 from the application process, how do we interpret the output. Whether it will be count as case A or case B?

Matthieu Brucher
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zevskiel
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1 Answers1

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That will really depend on your thresholding strategy.

First of all you have to choose a threshold between each of your target categories. You can:

  • either you choose to put arbitrary thresholds, that can be the midpoints (i.e. 0.6 between categories 0.4 and 0.8) or really anything else.
  • or else compute thresholds that reduce the classification error, which can be done by averaging best working threshold values over several test runs.

Then you have to choose what to do when your output values falls exactly on a threshold, that is really up to you, you can either choose to classify it "to the left", "to the right" or even make your network say that it can't classify the input. But keep in mind that in most cases it is quite unlikely to happen, at most it will end up close to the threshold but rarely exactly on it.

Cheers,

Dolma

Dolma
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