How can I use transfer learning in matlab for non image data

I have a non image data and I would like to use transfer learning to predict the response.

I generated 100 1D response data with each column representing a response at a particular gap (d). The generated data for the response is attached.

Gap variation

deld=(80E-9-10E-9)/100;

d=[10E-9:deld:80E-9];

I have tried using transfer learning but I am getting 100% accuracy. So, I am not sure this is right. Also, I could not predict any response from the model.

Please I need help.

Answer 1

[Udit06]

Hi Ambali,

You can refer to the following MathWorks documentation the explains how to leverage transfer learning for non-image data:

https://www.mathworks.com/help/deeplearning/ug/transfer-learning-with-audio-networks-in-deep-network-designer.html

I hope this helps.