How to use trained neural network using new data
21 views (last 30 days)
Show older comments
AHMAD FATHURRAHMAN
on 15 Jan 2023
Commented: Max Newman
on 4 Jun 2024
Hello esteemed friends, I need help. How can I use neural network to generate an output using 2 or 3 random new input data on trained neural network? For example using the abalone_dataset, I would train the neural network using input data (length, diameter, height, etc.) and the target data. After that, using only 2 to 3 input data (length and height only) to generate an output using the trained neural network.
3 Comments
Rajeev
on 16 Jan 2023
Based on what you have mentioned, you are trying to exploit 'transfer learning'.
You can refer to this link Get Started with Transfer Learning - MATLAB & Simulink (mathworks.com) to know more about it.
If you already have a pre-trained model, you can import it to the Deep Network Designer and modify the classification and output layers to get the output for your data.
Can you share the trained model that you want to modify?
Accepted Answer
Varun Sai Alaparthi
on 19 Jan 2023
Hello Ahmad,
I understand that you are looking for ways to get output from your trained model by giving random inputs. The function depends on your network type.
Output = net(X);
If you are using ‘dlnetwork’ or a network trained using ‘trainNetwork’ you can use the ‘predict’ function to get the output.
Output = predict(net,images);
If you have any further queries, please feel free to reply to my answer.
Sincerely,
Varun
1 Comment
Max Newman
on 4 Jun 2024
I trained a signal classifier but when I use predict it says that the "The input images must have a size of [96 64 1]." How can I use a trained network on signal data.
More Answers (0)
See Also
Categories
Find more on Sequence and Numeric Feature Data Workflows in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!