elmNN: Implementation of ELM (Extreme Learning Machine ) algorithm for SLFN ( Single Hidden Layer Feedforward Neural Networks )

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Training and predict functions for SLFN ( Single Hidden-layer Feedforward Neural Networks ) using the ELM algorithm. ELM algorithm differs from the traditional gradient-based algorithms for very short training times ( it doesn't need any iterative tuning, this makes learning time very fast ) and there is no need to set any other parameters like learning rate, momentum, epochs, etc.

Author
Alberto Gosso
Date of publication
2012-07-18 11:11:12
Maintainer
Alberto Gosso <gosso.alberto@gmail.com>
License
GPL (>= 2)
Version
1.0

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Man pages

elmNN-package
Implementation of ELM ( Extreme Learning Machine ) algorithm...
elmtrain
Training of a SLFN (Single Hidden-layer Feedforward Neural...
predict.elmNN
Calculate the output of the ELM-trained neural network
print.elmNN
Print a summary of the attributes of a trained neural network

Files in this package

elmNN
elmNN/MD5
elmNN/R
elmNN/R/hardlim.R
elmNN/R/poslin.R
elmNN/R/satlins.R
elmNN/R/randomMatrix.R
elmNN/R/tribas.R
elmNN/R/print.elmNN.R
elmNN/R/elmtrain.default.R
elmNN/R/elmtrain.formula.R
elmNN/R/hardlims.R
elmNN/R/elmtrain.R
elmNN/R/predict.elmNN.R
elmNN/NAMESPACE
elmNN/DESCRIPTION
elmNN/man
elmNN/man/elmNN-package.Rd
elmNN/man/print.elmNN.Rd
elmNN/man/predict.elmNN.Rd
elmNN/man/elmtrain.Rd