combining classification from 2 different NN , on two different datasets

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we have two diffrent datasets to be utilised for 2 different NN (classification type) and decision be made on results of both,eg if one has got defect in eye (retina dataset and iris dataset)
how to implement in the code?

Answers (1)

Abhishek Gupta
Abhishek Gupta on 22 Dec 2020
Hi,
As per my understanding, you want to train two different Neural Network on two different datasets for the classification problem. This task can be achieved by implementing and training two neural networks separately on the two datasets. After training, you can use these trained networks to make the prediction and then can compare the predictions at the same time.
The following documentation would help you in creating a simple network for classification: -
  5 Comments
Abhishek Gupta
Abhishek Gupta on 27 Dec 2020
For your problem, I would suggest you use Deep Network Designer instead, which will help you to create a customized network as described above. Here is the documentation link which might help you in getting started: -
Yogini Prabhu
Yogini Prabhu on 28 Dec 2020
thanks for suggesting the way to Deep network
but with a toddler baby, its difficult to migrate to a new area, (and I wish to achieve deadline of research paper to a quality submission ). i have used the app of nprtool (as said above).
kindly help with the results got, in the attached mat file

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