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Neural Network design problem

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salman abbasi
salman abbasi on 5 Mar 2021
Answered: Vineet Joshi on 26 Mar 2021
Hi
This will be my first ever neural network code. I am trying to implement feedforward netwrok. Let me explain what I am trying to achive.
I have a 1D vector P. This is the input to my network training. In the first round of network estimates(I have not decided yet how many layers will there be), a new vector P1 come as an output. Now i need to plug in the output to formula, say, Q=P1*scalar. I already have predefined Q range, say between 10 to 20. if the output P1, gives Q within this range, the network training needs to be stopped, else it should go for second round.
I have the following questions
  1. How to make this work
  2. On m furst round once the P1 does not meet the Q range, do i need to feed the updated P1, for second round of training
I appreciate the help in advance

Answers (1)

Vineet Joshi
Vineet Joshi on 26 Mar 2021
Hi
It looks like you are trying to scale your value P to a value Q where Q is between 10-20 and Q = P1 * scaler.
If you want to make this work, to being with, you need some labelled data to train the network.
The data can have the following columns.
P ------- Expected Q ------- Expected P1 (= Expected Q / scaler).
Once you have this data, you can fit a neural network between P (Inputs) and Expected P1 (Targets).
You can refer the following documentation to learn more about that.
You may also refer the following resources for more information.
Hope this helps.

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