Answers.Body: <p>Maybe, but it's likely overkill.  In hyperparameterization, random search, successive-halving or, lastly, evolutionary optimization is generally more than enough.  This is not to mention the dozen other methods people have proposed over the years.</p>
  
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Answers.CreationDate: 2024-12-23T19:09:09.820Z
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Answers.UserDisplayName: foreverska
Body: <p>I've developed a computer vision algorithm that produces a binary result from an image. This algorithm depends on a number of parameters.</p>
  <p>Is it possible to use a neural network to learn the best parameters, given the outcome of the execution of the algorithm on several images?</p>
  
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Comments.Text: are these parameters dependent on the image you are processing or they should be something generic?
Comments.UserDisplayName: Alberto
Tags: <neural-networks><computer-vision>
Title: Can a neural network be used to find the best parameters of an algorithm?
UserDisplayName: user3189362
ThreadText: # Can a neural network be used to find the best parameters of an algorithm?
  
  (Asked by: username_0 on 2024-12-23)
  
  I've developed a computer vision algorithm that produces a binary result from an image. This algorithm depends on a number of parameters.
  
  Is it possible to use a neural network to learn the best parameters, given the outcome of the execution of the algorithm on several images?
  
  **Tags:** neural-networks, computer-vision
  
  > **Comments:**
  > **username_1**: are these parameters dependent on the image you are processing or they should be something generic?  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2024-12-23. Score: 0
  
  Maybe, but it's likely overkill. In hyperparameterization, random search, successive-halving or, lastly, evolutionary optimization is generally more than enough. This is not to mention the dozen other methods people have proposed over the years.
  
  
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