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# Author: Babak Naimi, naimi.b@gmail.com
# Date : April 2018
# last update: March 2019
# Version 1.1
# Licence GPL v3
#-------------
methodInfo <- list(name=c('mlp','MLP','nnet.mlp','nnetMLP'),
packages='RSNNS',
modelTypes = c('pa','pb','ab','n'),
fitParams = list(formula='standard.formula',data='sdmDataFrame'),
fitSettings = list(size=10,maxit=500),
fitFunction = function(formula,data,...) {
x <- .getData.sdmMatrix(formula,data,normalize=TRUE)
y <- .getData.sdmY(formula,data)
mlp(x=x,y=y,...)
},
settingRules = NULL,
tuneParams = NULL,
predictParams=list(object='model',formula='standard.formula',newx='sdmDataFrame'),
predictSettings=NULL,
predictFunction=function(object,formula,newx) {
newx <- .getData.sdmMatrix(formula,newx,normalize=TRUE)
predict(object,newx)[,1]
},
#------ metadata (optional):
title='multilayer perceptron (MLP) network',
creator='Babak Naimi',
authors=c("Christoph Bergmeir et al. (for the package RSNNS)"), # authors of the main method
email='naimi.b@gmail.com',
url='http://r-gis.net',
citation=list(bibentry(bibtype='Manual',title = "SNNS Stuttgart Neural Network Simulator User Manual",
author = person("A. Zell, [aut]"),
year='1998',
organization="University of Stuttgart and WSI, University of Tübingen"
)
),
description="MLP is a type of Neural Network, a fully connected feedforward networks, and probably the most common network architecture in use."
)
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