RSNNS: train – R documentation

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train

Internal generic train function for rsnns objects

Description

The function calls SnnsRObject$train and saves the result in the current rsnns object. This function is used internally by the models (e.g. mlp) for training. Unless you are not about to implement a new model on the S3 layer you most probably don't want to use this function.

Usage

train(object, ...)

## S3 method for class 'rsnns'
train(object, inputsTrain, targetsTrain = NULL,
  inputsTest = NULL, targetsTest = NULL,
  serializeTrainedObject = TRUE, ...)

Arguments

`object`	the `rsnns` object
`...`	additional function parameters (currently not used)
`inputsTrain`	training input
`targetsTrain`	training targets
`inputsTest`	test input
`targetsTest`	test targets
`serializeTrainedObject`	parameter passed to `SnnsRObject$train`

Value

an rsnns object, to which the results of training have been added.

RSNNS

Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

v0.4-12

LGPL (>= 2) | file LICENSE

Authors

Christoph Bergmeir [aut, cre, cph], José M. Benítez [ths], Andreas Zell [ctb] (Part of original SNNS development team), Niels Mache [ctb] (Part of original SNNS development team), Günter Mamier [ctb] (Part of original SNNS development team), Michael Vogt [ctb] (Part of original SNNS development team), Sven Döring [ctb] (Part of original SNNS development team), Ralf Hübner [ctb] (Part of original SNNS development team), Kai-Uwe Herrmann [ctb] (Part of original SNNS development team), Tobias Soyez [ctb] (Part of original SNNS development team), Michael Schmalzl [ctb] (Part of original SNNS development team), Tilman Sommer [ctb] (Part of original SNNS development team), Artemis Hatzigeorgiou [ctb] (Part of original SNNS development team), Dietmar Posselt [ctb] (Part of original SNNS development team), Tobias Schreiner [ctb] (Part of original SNNS development team), Bernward Kett [ctb] (Part of original SNNS development team), Martin Reczko [ctb] (Part of original SNNS external contributors), Martin Riedmiller [ctb] (Part of original SNNS external contributors), Mark Seemann [ctb] (Part of original SNNS external contributors), Marcus Ritt [ctb] (Part of original SNNS external contributors), Jamie DeCoster [ctb] (Part of original SNNS external contributors), Jochen Biedermann [ctb] (Part of original SNNS external contributors), Joachim Danz [ctb] (Part of original SNNS development team), Christian Wehrfritz [ctb] (Part of original SNNS development team), Patrick Kursawe [ctb] (Contributors to SNNS Version 4.3), Andre El-Ama [ctb] (Contributors to SNNS Version 4.3)

Initial release

2019-09-16