Description Usage Arguments Value References Examples
Function for predictions from the results of ELM model fitting function.
1 | Elm.predict(TrainedElm, X.fit)
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TrainedElm |
an ELM object for which prediction is desired. |
X.fit |
Data matrix (numeric) containing the input values (predictors). |
The fitted values.
G.-B. Huang, Q.-Y. Zhu, C.-K. Siew (2006) Extreme learning machine: Theory and applications Neurocomputing 70 (2006) 489-501
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | set.seed(123)
attach(wtloss)
library("scales")
train.index <- sample(length(wtloss$Days),size=40)
#scaling the inputs/outputs
x.train <- rescale(as.matrix(wtloss$Days), to=c(-1,1))[train.index]
y.train <- rescale(as.matrix(wtloss$Weight), to=c(-1,1))[train.index]
x.test <- rescale(as.matrix(wtloss$Days), to=c(-1,1))[-train.index]
#training the ELM
trained.elm <- Elm.train(x.train,y.train,Number.hn =5)
#rescaling back the elm outputs
elm.fit.values <- rescale(trained.elm$predictionTrain,
to= range(as.matrix(wtloss$Weight)),from=c(-1,1))
elm.predicted.values <- rescale(Elm.predict(trained.elm, x.test),
to= range(as.matrix(wtloss$Weight)),from=c(-1,1))
oldpar <- par(mar = c(5.1, 4.1, 4.1, 4.1))
plot(wtloss$Days, wtloss$Weight, type = "p", ylab = "Weight (kg)",main="Weight Reduction",pch=20)
points(wtloss$Days[train.index], elm.fit.values,col=2,type='p',pch=20)
points(wtloss$Days[-train.index], elm.predicted.values,col=4,type='p',pch=20)
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