Description Usage Arguments Value Note Author(s) See Also Examples
Compute the prediction of a fuzzy system for the given input data.
1 | fugeR.predict(fuzzySystem, dataset)
|
fuzzySystem |
[NULL] The fuzzy system to use for computing the prediction. |
dataset |
[NULL] The data to use. |
prediction
, A data.frame containing the predictions.
The dataset must contain the same headers (in the same order) that the data
used to find the system with fugeR.run.
Alexandre Bujard, HEIG-VD, Jul'2012
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | ##
##
## Not run:
#We use the iris dataset for this example
#We need to convert the output in a numeric format.
data(iris)
OUT <- data.matrix(iris[5])[,1]
fIris <- cbind(iris[1:4], OUT)
In <- fIris[1:4]
Out <- fIris[5]
#Launch the evolution, fugeR.run will return
#the best fuzzy system found during the evolution
fuzzySystem <- fugeR.run( In,
Out,
generation=100, # Increase the number of generation for a better accuracy
population=100,
elitism=20,
verbose=TRUE,
threshold=NA,
sensiW=0.0,
speciW=0.0,
accuW=0.0,
rmseW=1.0,
maxRules=5,
maxVarPerRule=2,
labelsMf=3
)
#Plot the predicton given by the best fuzzy system found during the evolution
prediction <- fugeR.predict(fuzzySystem, In)
plot(prediction[[1]], ylim=c(1,max(unlist(Out))), col='blue', pch=21, axes=FALSE, ann=FALSE)
points(Out[[1]], col="red", pch=21)
axis(1)
axis(2, at=1:3, lab=c('setosa', 'versicolor', 'virginica'))
title(main='Fuzzy system prediction on Iris problem')
title(xlab="Cases")
title(ylab="Specie")
box()
legend(0.0, 3.0, c("Predicted","Actual"), cex=0.8,
col=c("blue","red"), pch=c(21,21))
#Display the fuzzy system
fugeR.summary(fuzzySystem)
## End(Not run)
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