Comments (1)
Hi, yes, that is possible, but it is not trivial to do it. First thing is that as the SNNS kernel is C, you'd need to implement them in C/C++.
The current learning functions are implemented in learn_f.cpp, and then you'd also need to add them to the function table in func_tbl.cpp . Both in the src/ folder of the package.
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Related Issues (19)
- RBF sites/links handling HOT 1
- How to implement a time-delay neural network using RSNNS? HOT 5
- Loading *.pat files HOT 1
- Where is old `loadNet()` HOT 1
- Unable To access repository for package installation in R HOT 1
- Activation Functions about RELU HOT 5
- Different results using Windows or Linux HOT 1
- Jordan segfault when used with more than one layer
- plotting function HOT 2
- Doubt about the forecast with RSNNS
- How to show the values of hidden nodes in a mlp model HOT 3
- Is it possible to use the RSNNS library to perform RBF interpolation when the target output is longer than the input? HOT 6
- predict method for pruned networks HOT 5
- A question for installing RSNNS HOT 4
- R crashes upon running mlp() HOT 3
- How do bias work at a mlp network? HOT 4
- Explanation for a command HOT 2
- Suggestion of init method HOT 9
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