inst/caretStack.R

library("caret")
library("mlbench")
library("pROC")
library("rpart")
library("caretEnsemble")
library("caTools")

data(Sonar)
set.seed(107)
inTrain <- createDataPartition(y = Sonar$Class, p = .75, list = FALSE)
training <- Sonar[ inTrain,]
testing <- Sonar[-inTrain,]
my_control <- trainControl(
  method="boot",
  number=25,
  savePredictions="final",
  classProbs=TRUE,
  index=createResample(training$Class, 25),
  summaryFunction=twoClassSummary
)

model_list <- caretList(
  Class~., data=training,
  trControl=my_control,
  methodList=c("glm", "rpart")
)

stackModel <- caretStack(
  model_list,
  method="glm",
  metric="ROC",
  trControl=trainControl(
    method="boot",
    number=10,
    savePredictions="final",
    classProbs=TRUE,
    summaryFunction=twoClassSummary
  )
)

preds <- predict(stackModel, newdata=testing, type="prob")
AndreGuerra123/BSSEmsembleR documentation built on May 24, 2019, 2:35 p.m.