Description Usage Arguments Value Author(s) References See Also Examples
Prediction of new data using kernelFactory.
1 2 3 |
object |
An object of class |
newdata |
A data frame with the same predictors as in the training data. |
predict.all |
TRUE or FALSE. If TRUE and rp and cp are 1 then the individual predictions of the random forest are returned. If TRUE and any of rp and cp or bigger than 1 then the predictions of all the members are returned. |
... |
Not used currently. |
A vector containing the response probabilities.
Authors: Michel Ballings and Dirk Van den Poel, Maintainer: Michel.Ballings@GMail.com
Ballings, M. and Van den Poel, D. (2013), Kernel Factory: An Ensemble of Kernel Machines. Expert Systems With Applications, 40(8), 2904-2913.
1 2 3 4 5 6 7 8 9 10 11 12 | #Credit Approval data available at UCI Machine Learning Repository
data(Credit)
#take subset (for the purpose of a quick example) and train and test
Credit <- Credit[1:100,]
train.ind <- sample(nrow(Credit),round(0.5*nrow(Credit)))
#Train Kernel Factory on training data
kFmodel <- kernelFactory(x=Credit[train.ind,names(Credit)!= "Response"],
y=Credit[train.ind,"Response"], method=random)
#Deploy Kernel Factory to predict response for test data
predictedresponse <- predict(kFmodel, newdata=Credit[-train.ind,names(Credit)!= "Response"])
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