Download Package `RSNNS`

RSNNS-package
3
SnnsRObject$getAllUnits . . . . . . . . . . . . . . . .
SnnsRObject$getAllUnitsTType . . . . . . . . . . . .
SnnsRObject$getCompleteWeightMatrix . . . . . . . .
SnnsRObject$getInfoHeader . . . . . . . . . . . . . .
SnnsRObject$getSiteDefinitions . . . . . . . . . . . .
SnnsRObject$getTypeDefinitions . . . . . . . . . . . .
SnnsRObject$getUnitDefinitions . . . . . . . . . . . .
SnnsRObject$getUnitsByName . . . . . . . . . . . . .
SnnsRObject$getWeightMatrix . . . . . . . . . . . . .
SnnsRObject$initializeNet . . . . . . . . . . . . . . .
SnnsRObject$predictCurrPatSet . . . . . . . . . . . .
SnnsRObject$resetRSNNS . . . . . . . . . . . . . . .
SnnsRObject$setTTypeUnitsActFunc . . . . . . . . .
SnnsRObject$setUnitDefaults . . . . . . . . . . . . .
SnnsRObject$somPredictComponentMaps . . . . . . .
SnnsRObject$somPredictCurrPatSetWinners . . . . .
SnnsRObject$somPredictCurrPatSetWinnersSpanTree
SnnsRObject$train . . . . . . . . . . . . . . . . . . .
SnnsRObject$whereAreResults . . . . . . . . . . . . .
som . . . . . . . . . . . . . . . . . . . . . . . . . . .
splitForTrainingAndTest . . . . . . . . . . . . . . . .
summary.rsnns . . . . . . . . . . . . . . . . . . . . .
toNumericClassLabels . . . . . . . . . . . . . . . . .
train . . . . . . . . . . . . . . . . . . . . . . . . . . .
vectorToActMap . . . . . . . . . . . . . . . . . . . .
weightMatrix . . . . . . . . . . . . . . . . . . . . . .
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Index
RSNNS-package
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Getting started with the RSNNS package
Description
The Stuttgart Neural Network Simulator (SNNS) is a library containing many standard implementations of neural networks. This package wraps the SNNS functionality to make it available from
within R.
Details
If you have problems using RSNNS, find a bug, or have suggestions, please contact the package
maintainer by email, instead of writing to the general R lists or contacting the authors of the original
SNNS software.
If you use the package, please cite the following work in your publications:
Bergmeir, C. and Benítez, J.M. (2012), Neural Networks in R Using the Stuttgart Neural Network
Simulator: RSNNS. Journal of Statistical Software, 46(7), 1-26. http://www.jstatsoft.org/
v46/i07/
The package has a hierarchical architecture with three levels: