Body: <p>I am attempting to train a neural network where I can say the following:</p>
  <p>For most inputs, I know the sign of the relationship between that input and several specific outputs. I.e. whatever set of values the inputs are set to, I can point to individual input and say that so long as the <em>other</em> inputs are unchanged, the output should monotonically increase/decrease as I change this input's value.</p>
  <p>This is not to say that the inputs don't interact with each other, they do, but the interaction never changes the sign (i.e. increasing vs decreasing) nature of the monotonic relationships between specific inputs and outputs.</p>
  <p>I am wondering how I can use this information to help my network learn fast and/or perform well.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-17T23:35:07.147Z
Comments.Text: Can you provide some more information about what your network needs to predict?
Comments.UserDisplayName: respectful
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-17T23:44:43.177Z
Comments.Text: Also, more information about the problem in general would be helpful. Like how do you know which inputs/outputs have the monotonic relationships?
Comments.UserDisplayName: respectful
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-18T07:07:39.947Z
Comments.Text: @respectful: I have 21 inputs and 3 outputs. Out of that I know with confidence the sign of a monotonic relationship between 18 of the inputs and all of the outputs. But due to a confidentiality agreement I can not say exactly what the problem is. I have in the ballpark of 100k input/output pairs for training.
Comments.UserDisplayName: Mick
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-12-21T16:01:08.767Z
Comments.Text: If you are familiar with latex could you formalize the problem statement within the question.
Comments.UserDisplayName: respectful
Tags: <neural-networks><feedforward-neural-networks>
Title: Can I help my neural network if I know the sign of the relationships between inputs and outputs
UserDisplayName: Mick
ThreadText: # Can I help my neural network if I know the sign of the relationships between inputs and outputs
  
  (Asked by: username_0 on 2021-12-17)
  
  I am attempting to train a neural network where I can say the following:
  
  For most inputs, I know the sign of the relationship between that input and several specific outputs. I.e. whatever set of values the inputs are set to, I can point to individual input and say that so long as the *other* inputs are unchanged, the output should monotonically increase/decrease as I change this input's value.
  
  This is not to say that the inputs don't interact with each other, they do, but the interaction never changes the sign (i.e. increasing vs decreasing) nature of the monotonic relationships between specific inputs and outputs.
  
  I am wondering how I can use this information to help my network learn fast and/or perform well.
  
  **Tags:** neural-networks, feedforward-neural-networks
  > **Comments:**
  > **username_1**: Can you provide some more information about what your network needs to predict?  
  > **username_1**: Also, more information about the problem in general would be helpful. Like how do you know which inputs/outputs have the monotonic relationships?  
  > **username_0**: @respectful: I have 21 inputs and 3 outputs. Out of that I know with confidence the sign of a monotonic relationship between 18 of the inputs and all of the outputs. But due to a confidentiality agreement I can not say exactly what the problem is. I have in the ballpark of 100k input/output pairs for training.  
  > **username_1**: If you are familiar with latex could you formalize the problem statement within the question.  
  
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  ## 0 answers
  
  