MATLAB: What is the difference between training, adapting, and learning in the neural network

Deep Learning Toolboxneural networktraining

I know that we can use different training functions. I do not know what is the difference between [net,tr] = adapt(net,inputs,targets) or net.trainFcn = 'traingdx';[net,tr] = train(net,inputs,targets) or net.adaptFcn = 'trains'; net.inputWeights{1,1}.learnFcn = 'learngd'; net.biases{1}.learnFcn = 'learngd';
I was wondering if some one has any experience about them?

Best Answer

NN learning is the process of modifying net parameters to try to achieve a goal.
I interpret adaptation as learning from a sequence of I/O examples where parameters are updated after each presentation of a single example. I equate this with the term "sequential learning"
I interpret training as learning from a group of I/O examples where parameters are updated after each presentation of the whole group. I equate this with the term "batch learning"
The official definitions may differ. If you find some, please post the references.
For any function:
1.Use the help and doc commands to obtain the online documentation and a simple example
2. Use the type command to see the source code.
3. Use the lookfor command to find ALL instances of a term in the help section of ANY function
For example try
 lookfor learn
and
 lookfor train
Hope this helps.
  • Thank you for formally accepting my answer*
Greg
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