Comments (1)
It is there in the low-level interface, as
snnsObject$loadNet(...)
Have a look at some of the low-level demos, like mlp_irisSnnsR.R
If you only use the high-level functions, like mlp(), elman() jordan(), etc., then simply saving and loading the R objects to RData files should work, due to the implemented object serialization mechanism, which will take care of this.
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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
- How to assign new learning algorithm ? 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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