Relation between input data points and hyper parameters that needs to be tuned

diyasingh - 2021-07-02T09:23:05+00:00

Question: Relation between input data points and hyper parameters that needs to be tuned

Hi All,   Can anyone please let me know the relationship between the number of input data points and the hyperparameters/number of layers that needs to be present in any machine learning model?

Related Questions

Expert Answer

Kshitij Singh answered . 2025-11-20

 [ I N]  = size(input)
 [ O N ] = size(target)

 % (MATLAB DEFAULT)
   Ntst    = round(0.15*N)
   Nval    = Ntst
   Ntrn    = N-(Ntst+Nval)%  ~ 0.7*N

 % Design parameters 
   Ndes = Ntrn*O           % No. of design equations ~ 0.7*N*O
   H                       % No. of hidden nodes for I-H-O net
   Nw   = (I+1)*H+(H+1)*O  % No. of unknown weights

 Require  Ndes >= Nw   ==> H <= Hub = (Ntrn*O-O)/(I+O+1)
 Desire   Ndes >> Nw   ==> H << Hub

         MSE < = 0.01*var(target',1)   % Rsquare >= 0.99

My approach:

 1. Apply the requirement to the training data
 2. Loop over H to find the minimum H to satisfy the 
    requirement.

Not satisfied with the answer ?? ASK NOW