0

I need to input data conditionally to my deep network. In order to explain cases, I'd like to give an example. Assume that I have a 50-attribute dataset. For some attributes, a specific part of hidden layers is responsible, and for others, a different part is responsible. Also, for some cases, the same parts of the hidden layers might intersect. I think I can decide which attributes must go which hidden neurons in the input layer by using some kind of if-else block. However, I could not figure out how.

My current idea

I can enter an identity element for some attributes. For example, I have att1, att2, att3, etc. I have ins1, ins2, etc. For ins1 -> att1 = 0.5, att2 = 0.2, att3 = None For ins2 -> att1 = 0.1, att2 = None, att3 = None

But, if I do this approach, the number of attributes for an instance becomes bigger unnecessarily.

End of my current idea

Are there any opinions on this? Should I rearrange my excel file or is there any way to use if-else conditions? Regards,

Mehmet Cengiz
  • 1
  • 1
  • This is very confusing, so to clarify: You have (or want?) a neural network that has that capacity to accept all 50 attributes, BUT is able to only accept a subset of them at a time? So you can input attributes [2,5,7] and nothing else? Or am I misunderstanding – Recessive Jul 09 '21 at 06:16
  • Hello. Welcome to AI SE. Could you please put your **specific** question in the title (to give an idea of what your question is to people that scroll down the list of questions)? – nbro Jul 09 '21 at 20:54

0 Answers0